{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This notebook demonstrates how to create an analysis ready spatialite database for borehoel data. All data has been processed filtered and the depths corrected onto to metres below ground level. Induction and gamma data are resampled to 5cm intervals and are on the same table.\n",
    "\n",
    "Neil Symington neil.symington@ga.gov.au"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\h5py\\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    }
   ],
   "source": [
    "import shapely.wkb\n",
    "import shapely.wkt\n",
    "from shapely.geometry import Point\n",
    "import os, glob\n",
    "import pandas as pd\n",
    "# sqlite/spatialite\n",
    "from sqlalchemy import create_engine, event, ForeignKey\n",
    "from sqlalchemy import Column, Integer, String, Float, Date, Boolean\n",
    "from sqlalchemy.ext.declarative import declarative_base\n",
    "from sqlalchemy.orm import relationship\n",
    "from sqlite3 import dbapi2 as sqlite\n",
    "import sys\n",
    "from pyproj import Proj, transform\n",
    "import lasio\n",
    "import sqlite3\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "import datetime\n",
    "import math\n",
    "\n",
    "# deal with the different setup of hydrogeol_utils\n",
    "if os.getlogin().lower() == 'u19955':\n",
    "    sys.path.append(r'\\\\prod.lan\\active\\proj\\futurex\\Common\\Working\\Mike\\GitHub\\hydrogeol_utils\\\\')\n",
    "\n",
    "from hydrogeol_utils.borehole_utils import extract_all_boredata_by_simple_query \n",
    "from hydrogeol_utils.plotting_utils import drawCompLog \n",
    "from hydrogeol_utils.db_utils import makeCon, closeCon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Neil Symington's local configuration\n",
    "DB_ROOT = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\"\n",
    "SPATIALITE_PATH = r'C:\\mod_spatialite-4.3.0a-win-amd64'\n",
    "\n",
    "# Add spatialite dll to path\n",
    "os.environ['PATH'] = SPATIALITE_PATH + ';' + os.environ['PATH']\n",
    "\n",
    "DB_PATH = os.path.join(DB_ROOT, r\"East_Kimberley_borehole_data.sqlite\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "PermissionError",
     "evalue": "[WinError 32] The process cannot access the file because it is being used by another process: '\\\\\\\\prod.lan\\\\active\\\\proj\\\\futurex\\\\East_Kimberley\\\\Working\\\\SharedWorkspace\\\\Bores_working\\\\compilation\\\\spatialite\\\\East_Kimberley_borehole_data.sqlite'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-3-c94e86a511c2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mDB_PATH\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 4\u001b[1;33m         \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mDB_PATH\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mPermissionError\u001b[0m: [WinError 32] The process cannot access the file because it is being used by another process: '\\\\\\\\prod.lan\\\\active\\\\proj\\\\futurex\\\\East_Kimberley\\\\Working\\\\SharedWorkspace\\\\Bores_working\\\\compilation\\\\spatialite\\\\East_Kimberley_borehole_data.sqlite'"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "if os.path.exists(DB_PATH):\n",
    "        os.remove(DB_PATH)\n",
    "\n",
    "        \n",
    "engine = create_engine('sqlite:///' + DB_PATH, module=sqlite, echo=False)\n",
    "\n",
    "@event.listens_for(engine, 'connect')\n",
    "def connect(dbapi_connection, connection_rec):\n",
    "    dbapi_connection.enable_load_extension(True)\n",
    "    dbapi_connection.execute('SELECT load_extension(\"mod_spatialite\")')\n",
    "\n",
    "# create spatialite metadata\n",
    "print('creating spatial metadata...')\n",
    "engine.execute(\"SELECT InitSpatialMetaData(1);\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create schema\n",
    "Base = declarative_base()\n",
    "\n",
    "class Boreholes(Base):\n",
    "    __tablename__ = 'borehole'\n",
    "    borehole_id = Column(Integer, index=True, primary_key=True)\n",
    "    borehole_name = Column(\"Borehole_name\", String(20))\n",
    "    alternative_name = Column(\"Alternative_name\", String(20))\n",
    "    easting = Column(\"Easting\", Float)\n",
    "    northing = Column(\"Northing\", Float)\n",
    "    elevation = Column(\"Ground_elevation_mAHD\", Float)\n",
    "    induction = Column(\"Induction_acquired\", Boolean)\n",
    "    gamma = Column(\"Gamma_acquired\", Boolean)\n",
    "    javelin = Column(\"Javelin_acquired\", Boolean)\n",
    "    hylogger_core = Column(\"Hylogger_acquired_on_core\", Boolean)\n",
    "    hylogger_chips = Column(\"Hylogger_acquired_on_chips\", Boolean)\n",
    "    lithology = Column(\"Lithology_available\", Boolean)\n",
    "    ECpH = Column(\"EC_pH_acquired\", Boolean)\n",
    "    swl = Column(\"SWL_available\", Boolean)\n",
    "    construction = Column(\"Construction_available\", Boolean)\n",
    "    magsus = Column(\"MagSus_available\", Boolean)\n",
    "    AEM = Column(\"AEM_conductivity_available\", Boolean)\n",
    "    geometry = Column(String)\n",
    "\n",
    "    \n",
    "class Induction_gamma_data(Base):\n",
    "    __tablename__ = 'induction_gamma_data'\n",
    "    induction_gamma_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth = Column(\"Depth\", Float)\n",
    "    conductivity = Column(\"Apparent_conductivity\", Float)\n",
    "    gamma_calibrated = Column(\"Gamma_calibrated\", Float)\n",
    "    K = Column(\"K\", Float)\n",
    "    U = Column(\"U\", Float)\n",
    "    Th = Column(\"Th\", Float)\n",
    "    GR = Column(\"GR\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "\n",
    "class Borehole_NMR_data(Base):\n",
    "    __tablename__ = 'boreholeNMR_data'\n",
    "    bNMR_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth = Column(\"Depth\", Float)\n",
    "    totalf = Column(\"Total_water_content\", Float)\n",
    "    clayf = Column(\"Clay_water_content\", Float)\n",
    "    capf = Column(\"Capillary_water_content\", Float)\n",
    "    free = Column(\"Free_water_content\", Float)\n",
    "    T2 = Column(\"T2\", Float)\n",
    "    K = Column(\"K_sdr\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "    \n",
    "class Lithology(Base):\n",
    "    __tablename__ = 'borehole_lithology'\n",
    "    lithology_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth_from = Column(\"Depth_from\", Float)\n",
    "    depth_to = Column(\"Depth_to\", Float)\n",
    "    lithology_type = Column(\"Lithology_type\", String(40))\n",
    "    lithdescription = Column(\"Lithology_description\", String(250))\n",
    "    clay_frac = Column(\"Clay_fraction\", String(1))\n",
    "    silt_frac = Column(\"Silt_fraction\", String(1))\n",
    "    fsand_frac = Column(\"Fine_sand_fraction\", String(1))\n",
    "    msand_frac = Column(\"Medium_sand_fraction\", String(1))\n",
    "    csand_frac = Column(\"Coarse_sand_fraction\", String(1))\n",
    "    granule_frac = Column(\"Granule_fraction\", String(1))\n",
    "    pebble_frac = Column(\"Pebble_fraction\", String(1))\n",
    "    sorting = Column(\"Sorting\", String(1))\n",
    "    rounding = Column(\"Rounding\", String(1))\n",
    "    weathering = Column(\"Weathering\", String(1))\n",
    "    \n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "\n",
    "class EC_pH(Base):\n",
    "    __tablename__ = 'pore_fluid_EC_pH'\n",
    "    EC_pH_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth = Column(\"Depth\", Float)\n",
    "    EC = Column(\"EC\", Float)\n",
    "    pH = Column(\"pH\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "    \n",
    "    \n",
    "class SWL(Base):\n",
    "    __tablename__ = 'standing_water_level'\n",
    "    SWL_id = Column(Integer, index=True, primary_key=True)\n",
    "    date = Column(\"Date\", Date)\n",
    "    depth = Column(\"Depth\", Float)\n",
    "    Measurer = Column(\"Measurer\", String(30))\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "    \n",
    "class Construction(Base):\n",
    "    __tablename__ = 'borehole_construction'\n",
    "    construction_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth_from = Column(\"Depth_from\", Float)\n",
    "    depth_to = Column(\"Depth_to\", Float)\n",
    "    Measurer = Column(\"Measurer\", String(30))\n",
    "    Construction_name = Column(\"Construction_name\", String(20))\n",
    "    Construction_type = Column(\"Construction_type\", String(20))\n",
    "    Construction_materials = Column(\"Construction_materials\", String(20))\n",
    "    Internal_diameter = Column(\"Internal_diameter\", Float)\n",
    "    Property = Column(\"Property\", String(5))\n",
    "    Property_size = Column(\"Property_size\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "    \n",
    "class MagSus(Base):\n",
    "    __tablename__ = 'magnetic_susceptibility'\n",
    "    magsus_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth = Column(\"Depth\", Float)\n",
    "    magsus = Column(\"Magnetic_susceptibility\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")\n",
    "    \n",
    "class AEM_conductivity(Base):\n",
    "    __tablename__ = \"representative_AEM_bulk_conductivity\"\n",
    "    bulk_conductivity_id = Column(Integer, index=True, primary_key=True)\n",
    "    depth_from = Column(\"Depth_from\", Float)\n",
    "    depth_to = Column(\"Depth_to\", Float)\n",
    "    conductivity = Column(\"Bulk_conductivity\", Float)\n",
    "    \n",
    "    borehole_id = Column(Integer, ForeignKey('borehole.borehole_id'))\n",
    "    borehole_header = relationship(\"Boreholes\")    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Base.metadata.create_all(engine)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "infile = os.path.join(DB_ROOT, \"Boreholes_header.csv\")\n",
    "\n",
    "df_header = pd.read_csv(infile)\n",
    "\n",
    "df_header[\"Induction_acquired\"] = 0\n",
    "df_header[\"Gamma_acquired\"] = 0\n",
    "df_header[\"Javelin_acquired\"] = 0\n",
    "df_header[\"Hylogger_chips_acquired\"] = 0\n",
    "df_header[\"Hylogger_core_acquired\"] = 0\n",
    "df_header[\"lithology_description\"] = 0\n",
    "df_header[\"EC_pH_acquired\"] = 0\n",
    "df_header['SWL_available'] = 0\n",
    "df_header['Construction_available'] = 0\n",
    "df_header['MagSus_available'] = 0\n",
    "df_header['AEM_conductivity_available'] = 0\n",
    "\n",
    "\n",
    "df_header['easting'] = [shapely.wkt.loads(x).x for x  in df_header[\"geometry\"]]\n",
    "df_header['northing'] = [shapely.wkt.loads(y).y for y  in df_header[\"geometry\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BOREHOLE_NAME</th>\n",
       "      <th>ENO</th>\n",
       "      <th>ALTERNATE_NAMES</th>\n",
       "      <th>geometry</th>\n",
       "      <th>ground_elevation_(mAHD)</th>\n",
       "      <th>Induction_acquired</th>\n",
       "      <th>Gamma_acquired</th>\n",
       "      <th>Javelin_acquired</th>\n",
       "      <th>Hylogger_chips_acquired</th>\n",
       "      <th>Hylogger_core_acquired</th>\n",
       "      <th>lithology_description</th>\n",
       "      <th>EC_pH_acquired</th>\n",
       "      <th>SWL_available</th>\n",
       "      <th>Construction_available</th>\n",
       "      <th>MagSus_available</th>\n",
       "      <th>AEM_conductivity_available</th>\n",
       "      <th>easting</th>\n",
       "      <th>northing</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>RN039880</td>\n",
       "      <td>627064</td>\n",
       "      <td>17BP07I</td>\n",
       "      <td>POINT (468859.889 8331473.34)</td>\n",
       "      <td>93.167</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>468859.889</td>\n",
       "      <td>8331473.34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   BOREHOLE_NAME     ENO ALTERNATE_NAMES                       geometry  \\\n",
       "16      RN039880  627064         17BP07I  POINT (468859.889 8331473.34)   \n",
       "\n",
       "    ground_elevation_(mAHD)  Induction_acquired  Gamma_acquired  \\\n",
       "16                   93.167                   0               0   \n",
       "\n",
       "    Javelin_acquired  Hylogger_chips_acquired  Hylogger_core_acquired  \\\n",
       "16                 0                        0                       0   \n",
       "\n",
       "    lithology_description  EC_pH_acquired  SWL_available  \\\n",
       "16                      0               0              0   \n",
       "\n",
       "    Construction_available  MagSus_available  AEM_conductivity_available  \\\n",
       "16                       0                 0                           0   \n",
       "\n",
       "       easting    northing  \n",
       "16  468859.889  8331473.34  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_header[df_header['ENO'] == 627064]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def update_availability_flag(df_header, channels, eno):\n",
    "    # find index for given eno\n",
    "    index = df_header[df_header[\"ENO\"] == eno].index\n",
    "    \n",
    "    # Check induciton\n",
    "    if (\"INDUCTION_CALIBRATED\" in channels) or (\"INDUCTION_BOREHOLE_COMPENSATED\" in channels):\n",
    "        df_header.at[index, \"Induction_acquired\"] = 1\n",
    "    \n",
    "    # Check gamma\n",
    "    if (\"GAMMA_CALIBRATED\" in channels) or (\"GR\" in channels) or (\"K\" in channels) or \\\n",
    "        (\"U\" in channels) or (\"Th\" in channels):\n",
    "        df_header.at[index, \"Gamma_acquired\"] = 1\n",
    "    \n",
    "    return df_header\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\pandas\\core\\frame.py:6201: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=True'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass sort=False\n",
      "\n",
      "  sort=sort)\n"
     ]
    }
   ],
   "source": [
    "# Now lets read in the induction gamma data\n",
    "\n",
    "las_dir = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Data\\Processed\\Geophysics\\Induction_gamma\\EK_filtered_induction_gamma\"\n",
    "\n",
    "\n",
    "# Create empty dataframe into which to append the data\n",
    "\n",
    "df_indgam = pd.DataFrame(columns = [\"borehole_id\", \"Depth_mBGL\"])\n",
    "# Iterate through the las files\n",
    "os.chdir(las_dir)\n",
    "\n",
    "for file in glob.glob('*.LAS'):\n",
    "    las = lasio.read(file)\n",
    "    df_logs = las.df()\n",
    "    \n",
    "    # Get the eno and ref datum\n",
    "    datum = las.well.APD.value\n",
    "    eno = las.well.UWI.value\n",
    "    \n",
    "    # Update the df_header dataframe with the inclusion or otherwise of\n",
    "    # induction and gamma\n",
    "    df_header = update_availability_flag(df_header, df_logs.columns, eno)\n",
    "    \n",
    "    df_logs[\"borehole_id\"] = eno\n",
    "    \n",
    "    # Now make the convert the depth reference to mBGL\n",
    "    df_logs[\"Depth_mBGL\"] = df_logs.index - datum\n",
    "    \n",
    "    # Append\n",
    "    df_indgam = df_indgam.append(df_logs) \n",
    "\n",
    "df_indgam.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'Depth_mBGL', 'GAMMA_CALIBRATED', 'GR',\n",
       "       'INDUCTION_BOREHOLE_COMPENSATED', 'INDUCTION_CALIBRATED', 'K', 'TH',\n",
       "       'U', 'borehole_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_indgam.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Convert to S/m\n",
    "df_indgam['INDUCTION_BOREHOLE_COMPENSATED'] = df_indgam['INDUCTION_BOREHOLE_COMPENSATED'].values /1000.\n",
    "df_indgam['INDUCTION_CALIBRATED'] = df_indgam['INDUCTION_CALIBRATED'].values /1000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we import the javelin data\n",
    "infile = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\borehole_NMR\\bNMR_data_compiled.csv\"\n",
    "\n",
    "df_bnmr_data = pd.read_csv(infile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now update the flag for NMR data\n",
    "\n",
    "bnmr_enos = df_bnmr_data.borehole_id.unique()\n",
    "\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in bnmr_enos:\n",
    "        df_header.at[index, \"Javelin_acquired\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now bring in the lithology data\n",
    "\n",
    "infile = r\"R:\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\sonic_lithology\\ALLHOLES_RAW_NS.csv\"\n",
    "\n",
    "df_lithology = pd.read_csv(infile)\n",
    "\n",
    "lithology_enos = df_lithology.borehole_id.unique()\n",
    "\n",
    "# header table gets true if lithology data is available\n",
    "# for this site\n",
    "\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in lithology_enos:\n",
    "        df_header.at[index, \"lithology_description\"] = 1\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\IPython\\core\\interactiveshell.py:2698: DtypeWarning: Columns (14,66) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "# NOw we bring in the hylogger data\n",
    "hylog_dir = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\hylogger\"\n",
    "\n",
    "df_hylogs = pd.read_csv(os.path.join(hylog_dir, \"EK_hylogg_results_core.csv\"))\n",
    "\n",
    "df_hychips = pd.read_csv(os.path.join(hylog_dir, \"EK_hylogg_results_chips.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['AMPHIBOLE_(U_TIR_TSA707_Group)', 'Actinolite_(U_TIR_TSA707_Mineral)',\n",
       "       'Albite_(U_TIR_TSA707_Mineral)', 'Alunite-K_(U_TIR_TSA707_Mineral)',\n",
       "       'Alunite-Na_(U_TIR_TSA707_Mineral)',\n",
       "       'AmphiboleML48_(U_TIR_TSA707_Mineral)',\n",
       "       'Andesine_(U_TIR_TSA707_Mineral)', 'Apatite_(U_TIR_TSA707_Mineral)',\n",
       "       'Aspectral_(U_TIR_TSA707_Mineral)', 'Bytownite_(U_TIR_TSA707_Mineral)',\n",
       "       ...\n",
       "       'Prehnite_(U_SWIR_TSA705_Mineral)',\n",
       "       'Pyrophyllite_(U_SWIR_TSA705_Mineral)',\n",
       "       'SMECTITE_(U_SWIR_TSA705_Group)', 'SULPHATE_(U_SWIR_TSA705_Group)',\n",
       "       'Sample_Comment_y', 'Saponite_(U_SWIR_TSA705_Mineral)',\n",
       "       'Siderite_(U_SWIR_TSA705_Mineral)', 'Topaz_(U_SWIR_TSA705_Mineral)',\n",
       "       'Tremolite_(U_SWIR_TSA705_Mineral)',\n",
       "       'WHITE-MICA_(U_SWIR_TSA705_Group)'],\n",
       "      dtype='object', length=107)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_hylogs.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now update the flag for NMR data\n",
    "\n",
    "hylog_core_enos = df_hylogs.borehole_id.unique()\n",
    "hylog_chips_enos = df_hychips.borehole_id.unique()\n",
    "\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in hylog_core_enos:\n",
    "        df_header.at[index, \"Hylogger_core_acquired\"] = 1\n",
    "        \n",
    "    if row['ENO'] in hylog_chips_enos:\n",
    "        df_header.at[index, \"Hylogger_chips_acquired\"] = 1\n",
    "    \n",
    "# REmove from memory\n",
    "\n",
    "df_hylogs = None\n",
    "df_hychips = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bring in the EC pH data\n",
    "df_ECpH = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\EC_pH\\EC_pH_sonic.csv\")\n",
    "\n",
    "ECpH_enos = df_ECpH['Borehole_eno'].values\n",
    "\n",
    "# Update the flags\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in ECpH_enos:\n",
    "        df_header.at[index, \"EC_pH_acquired\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# COnvert to S/m\n",
    "\n",
    "df_ECpH['EC Value'] = df_ECpH['EC Value'].values * 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bring in the SWL data\n",
    "df_swl = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\SWLs\\EK_adjusted_SWL.csv\")\n",
    "\n",
    "swl_enos = df_swl['ENO'].values\n",
    "\n",
    "# Create datetime object\n",
    "df_swl['Date Measured'] = pd.to_datetime(df_swl['Date Measured'], dayfirst = True,\n",
    "               format = \"%d/%m/%Y\")\n",
    "\n",
    "# Update the flags\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in swl_enos:\n",
    "        df_header.at[index, \"SWL_available\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Bring in construction\n",
    "\n",
    "df_const = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\construction\\GA_EK_Boreholes_Construction.csv\")\n",
    "\n",
    "constr_enos = df_const['ENO'].values\n",
    "\n",
    "# Update the flags\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in constr_enos:\n",
    "        df_header.at[index, \"Construction_available\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_magsus = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\mag_sus\\mag_sus_vfinal.csv\")\n",
    "\n",
    "magsus_enos = df_magsus['Borehole_eno'].values\n",
    "\n",
    "\n",
    "# Update the flags\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in magsus_enos:\n",
    "        df_header.at[index, 'MagSus_available'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_aem = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\AEM\\EK_AEM_borehole_interpolated_duplicates_removed.csv\")\n",
    "aem_enos = df_aem['borehole_id'].values\n",
    "\n",
    "\n",
    "# Update the flags\n",
    "for index, row in df_header.iterrows():\n",
    "    if row['ENO'] in aem_enos:\n",
    "        df_header.at[index, 'AEM_conductivity_available'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BOREHOLE_NAME</th>\n",
       "      <th>ENO</th>\n",
       "      <th>ALTERNATE_NAMES</th>\n",
       "      <th>geometry</th>\n",
       "      <th>ground_elevation_(mAHD)</th>\n",
       "      <th>Induction_acquired</th>\n",
       "      <th>Gamma_acquired</th>\n",
       "      <th>Javelin_acquired</th>\n",
       "      <th>Hylogger_chips_acquired</th>\n",
       "      <th>Hylogger_core_acquired</th>\n",
       "      <th>lithology_description</th>\n",
       "      <th>EC_pH_acquired</th>\n",
       "      <th>SWL_available</th>\n",
       "      <th>Construction_available</th>\n",
       "      <th>MagSus_available</th>\n",
       "      <th>AEM_conductivity_available</th>\n",
       "      <th>easting</th>\n",
       "      <th>northing</th>\n",
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       "  </thead>\n",
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       "      <td>478993.383</td>\n",
       "      <td>8335027.204</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17BP03I</td>\n",
       "      <td>621623</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (469012.153 8340498.65)</td>\n",
       "      <td>109.525</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>469012.153</td>\n",
       "      <td>8340498.650</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17BP04I</td>\n",
       "      <td>621624</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (462705.715 8344019.122)</td>\n",
       "      <td>66.474</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>462705.715</td>\n",
       "      <td>8344019.122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17BP05I</td>\n",
       "      <td>621625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (461179.05 8347241.926)</td>\n",
       "      <td>41.333</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>461179.050</td>\n",
       "      <td>8347241.926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RN029663</td>\n",
       "      <td>626981</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (509738 8297777)</td>\n",
       "      <td>14.936</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>509738.000</td>\n",
       "      <td>8297777.000</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>RN034821</td>\n",
       "      <td>626984</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (514784 8313635)</td>\n",
       "      <td>12.281</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>514784.000</td>\n",
       "      <td>8313635.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>RN029660</td>\n",
       "      <td>626986</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (500047.884 8295266.378)</td>\n",
       "      <td>19.217</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>500047.884</td>\n",
       "      <td>8295266.378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>RN029665</td>\n",
       "      <td>626987</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (512860 8302461)</td>\n",
       "      <td>11.873</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>512860.000</td>\n",
       "      <td>8302461.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>RN029653</td>\n",
       "      <td>626988</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (514021 8301501)</td>\n",
       "      <td>12.904</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>514021.000</td>\n",
       "      <td>8301501.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RN029656</td>\n",
       "      <td>626989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (504845 8293381)</td>\n",
       "      <td>17.650</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>504845.000</td>\n",
       "      <td>8293381.000</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>RN029666</td>\n",
       "      <td>626990</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (518194 8307268)</td>\n",
       "      <td>9.266</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>518194.000</td>\n",
       "      <td>8307268.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>RN029662</td>\n",
       "      <td>626991</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (500590 8288080)</td>\n",
       "      <td>18.952</td>\n",
       "      <td>1</td>\n",
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       "      <td>500590.000</td>\n",
       "      <td>8288080.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RN030826</td>\n",
       "      <td>626992</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (501892 8274331)</td>\n",
       "      <td>28.793</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>501892.000</td>\n",
       "      <td>8274331.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13BP01D</td>\n",
       "      <td>627061</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (473886.62 8333260.73)</td>\n",
       "      <td>84.040</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>473886.620</td>\n",
       "      <td>8333260.730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>81010175</td>\n",
       "      <td>627062</td>\n",
       "      <td>Yow Bore</td>\n",
       "      <td>POINT (470932 8351821)</td>\n",
       "      <td>6.308</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>470932.000</td>\n",
       "      <td>8351821.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>17BP06I</td>\n",
       "      <td>627063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (476482.346 8321899.871)</td>\n",
       "      <td>94.617</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>476482.346</td>\n",
       "      <td>8321899.871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>RN039880</td>\n",
       "      <td>627064</td>\n",
       "      <td>17BP07I</td>\n",
       "      <td>POINT (468859.889 8331473.34)</td>\n",
       "      <td>93.167</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>468859.889</td>\n",
       "      <td>8331473.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>RN039888</td>\n",
       "      <td>628981</td>\n",
       "      <td>18BP07-D</td>\n",
       "      <td>POINT (468836 8331457)</td>\n",
       "      <td>92.860</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>468836.000</td>\n",
       "      <td>8331457.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>RN040873</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>POINT (520144.76 8306293.88)</td>\n",
       "      <td>7.519</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>520144.760</td>\n",
       "      <td>8306293.880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>RN040879</td>\n",
       "      <td>635729</td>\n",
       "      <td>KR21a</td>\n",
       "      <td>POINT (523301.492 8314853.537)</td>\n",
       "      <td>4.575</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>523301.492</td>\n",
       "      <td>8314853.537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>RN040880</td>\n",
       "      <td>635730</td>\n",
       "      <td>KR22a</td>\n",
       "      <td>POINT (523640.009 8316422.357)</td>\n",
       "      <td>4.364</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>523640.009</td>\n",
       "      <td>8316422.357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>RN040782</td>\n",
       "      <td>635732</td>\n",
       "      <td>KR23</td>\n",
       "      <td>POINT (522411.732 8301368.526)</td>\n",
       "      <td>12.030</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>522411.732</td>\n",
       "      <td>8301368.526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>RN040874</td>\n",
       "      <td>635733</td>\n",
       "      <td>KR30</td>\n",
       "      <td>POINT (501830.614 8295403.07)</td>\n",
       "      <td>17.506</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>501830.614</td>\n",
       "      <td>8295403.070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>RN040877</td>\n",
       "      <td>635734</td>\n",
       "      <td>KR31</td>\n",
       "      <td>POINT (504915.931 8292360.686)</td>\n",
       "      <td>17.913</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>504915.931</td>\n",
       "      <td>8292360.686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>RN040878</td>\n",
       "      <td>635735</td>\n",
       "      <td>KR33</td>\n",
       "      <td>POINT (505309.448 8293856.701)</td>\n",
       "      <td>16.494</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>505309.448</td>\n",
       "      <td>8293856.701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>RN040783</td>\n",
       "      <td>635736</td>\n",
       "      <td>KR36</td>\n",
       "      <td>POINT (509392.776 8307934.098)</td>\n",
       "      <td>16.490</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>509392.776</td>\n",
       "      <td>8307934.098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>RN040884</td>\n",
       "      <td>635737</td>\n",
       "      <td>KR38</td>\n",
       "      <td>POINT (507769.229 8299897.749)</td>\n",
       "      <td>12.462</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>507769.229</td>\n",
       "      <td>8299897.749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>RN040883</td>\n",
       "      <td>635738</td>\n",
       "      <td>KR40</td>\n",
       "      <td>POINT (514309.962 8298828.237)</td>\n",
       "      <td>17.673</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>514309.962</td>\n",
       "      <td>8298828.237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>RN040881</td>\n",
       "      <td>635739</td>\n",
       "      <td>KR45</td>\n",
       "      <td>POINT (500051.985 8295681.132)</td>\n",
       "      <td>18.799</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>500051.985</td>\n",
       "      <td>8295681.132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>RN040882</td>\n",
       "      <td>635740</td>\n",
       "      <td>KR46</td>\n",
       "      <td>POINT (500053.109 8296644.456)</td>\n",
       "      <td>18.357</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>500053.109</td>\n",
       "      <td>8296644.456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>RN039890</td>\n",
       "      <td>635923</td>\n",
       "      <td>18BP01-D</td>\n",
       "      <td>POINT (479026 8334987)</td>\n",
       "      <td>41.337</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>479026.000</td>\n",
       "      <td>8334987.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>RN039169</td>\n",
       "      <td>635957</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (502856 8296555)</td>\n",
       "      <td>17.107</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>502856.000</td>\n",
       "      <td>8296555.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>RN040310</td>\n",
       "      <td>635958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (507701 8296949)</td>\n",
       "      <td>15.018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>507701.000</td>\n",
       "      <td>8296949.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>RN040311</td>\n",
       "      <td>635959</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (513882 8298826)</td>\n",
       "      <td>18.267</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>513882.000</td>\n",
       "      <td>8298826.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>RN040315</td>\n",
       "      <td>635960</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (518761 8298429)</td>\n",
       "      <td>19.814</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>518761.000</td>\n",
       "      <td>8298429.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>RN007412</td>\n",
       "      <td>636181</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (505548.7 8292329.3)</td>\n",
       "      <td>17.345</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>505548.700</td>\n",
       "      <td>8292329.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>RN029933</td>\n",
       "      <td>636182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (533361.5 8319410.2)</td>\n",
       "      <td>9.683</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>533361.500</td>\n",
       "      <td>8319410.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>RN029945</td>\n",
       "      <td>636183</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (520250.6 8296657.3)</td>\n",
       "      <td>16.924</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>520250.600</td>\n",
       "      <td>8296657.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>RN030884</td>\n",
       "      <td>636184</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (499585 8274061)</td>\n",
       "      <td>28.644</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>499585.000</td>\n",
       "      <td>8274061.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>RN030885</td>\n",
       "      <td>636185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (499613.8 8274026.4)</td>\n",
       "      <td>28.689</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>499613.800</td>\n",
       "      <td>8274026.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>RN038543</td>\n",
       "      <td>636186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (538158 8333350)</td>\n",
       "      <td>7.480</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>538158.000</td>\n",
       "      <td>8333350.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>RN039870</td>\n",
       "      <td>636187</td>\n",
       "      <td>17BP02I</td>\n",
       "      <td>POINT (468839 8347946.281)</td>\n",
       "      <td>44.489</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>468839.000</td>\n",
       "      <td>8347946.281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>FW1mon</td>\n",
       "      <td>636188</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (470862 8268419)</td>\n",
       "      <td>36.146</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>470862.000</td>\n",
       "      <td>8268419.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>10WP39</td>\n",
       "      <td>636189</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (486098.168 8295716.033)</td>\n",
       "      <td>23.257</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>486098.168</td>\n",
       "      <td>8295716.033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>10WP42</td>\n",
       "      <td>636190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (487500.84 8295383.694)</td>\n",
       "      <td>22.867</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>487500.840</td>\n",
       "      <td>8295383.694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>80918500</td>\n",
       "      <td>636191</td>\n",
       "      <td>KC10,Ord16</td>\n",
       "      <td>POINT (499481 8278726)</td>\n",
       "      <td>25.025</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>499481.000</td>\n",
       "      <td>8278726.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>80918219</td>\n",
       "      <td>636192</td>\n",
       "      <td>Ord37</td>\n",
       "      <td>POINT (450804 8281036)</td>\n",
       "      <td>16.941</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>450804.000</td>\n",
       "      <td>8281036.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>80918517</td>\n",
       "      <td>636193</td>\n",
       "      <td>WBS1155</td>\n",
       "      <td>POINT (497352 8285299)</td>\n",
       "      <td>20.364</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>497352.000</td>\n",
       "      <td>8285299.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>80918284</td>\n",
       "      <td>636194</td>\n",
       "      <td>Ord24</td>\n",
       "      <td>POINT (499770 8287091)</td>\n",
       "      <td>18.944</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>499770.000</td>\n",
       "      <td>8287091.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>81010136</td>\n",
       "      <td>636195</td>\n",
       "      <td>WBS5080</td>\n",
       "      <td>POINT (497129 8293599)</td>\n",
       "      <td>20.660</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>497129.000</td>\n",
       "      <td>8293599.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>10WP32PB</td>\n",
       "      <td>636196</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (486513.137 8290539.107)</td>\n",
       "      <td>25.641</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>486513.137</td>\n",
       "      <td>8290539.107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>10WP46</td>\n",
       "      <td>636197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (486593.359 8295887.04)</td>\n",
       "      <td>22.991</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>486593.359</td>\n",
       "      <td>8295887.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>80918510</td>\n",
       "      <td>636198</td>\n",
       "      <td>KC13</td>\n",
       "      <td>POINT (495809.481 8277098.459)</td>\n",
       "      <td>25.753</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>495809.481</td>\n",
       "      <td>8277098.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>81070001</td>\n",
       "      <td>636200</td>\n",
       "      <td>10WP36</td>\n",
       "      <td>POINT (481885 8289596)</td>\n",
       "      <td>26.305</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>481885.000</td>\n",
       "      <td>8289596.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>80918511</td>\n",
       "      <td>636201</td>\n",
       "      <td>KC14</td>\n",
       "      <td>POINT (497960.303 8278737.019)</td>\n",
       "      <td>24.845</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>497960.303</td>\n",
       "      <td>8278737.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>80918301</td>\n",
       "      <td>636203</td>\n",
       "      <td>Ord40</td>\n",
       "      <td>POINT (441916 8283743)</td>\n",
       "      <td>7.232</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>441916.000</td>\n",
       "      <td>8283743.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>80918513</td>\n",
       "      <td>636204</td>\n",
       "      <td>KC3PB</td>\n",
       "      <td>POINT (498131.764 8284346.403)</td>\n",
       "      <td>21.279</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>498131.764</td>\n",
       "      <td>8284346.403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>80918508</td>\n",
       "      <td>636205</td>\n",
       "      <td>KC11</td>\n",
       "      <td>POINT (497425 8284141)</td>\n",
       "      <td>21.211</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>497425.000</td>\n",
       "      <td>8284141.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>KR58</td>\n",
       "      <td>635749</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (432985.0 8287369.0)</td>\n",
       "      <td>5.900</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>432985.000</td>\n",
       "      <td>8287369.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>IP02</td>\n",
       "      <td>635920</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (441693.0 8289537.0)</td>\n",
       "      <td>5.800</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>441693.000</td>\n",
       "      <td>8289537.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>71 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   BOREHOLE_NAME     ENO ALTERNATE_NAMES                        geometry  \\\n",
       "0        17BP01I  621622             NaN  POINT (478993.383 8335027.204)   \n",
       "1        17BP03I  621623             NaN   POINT (469012.153 8340498.65)   \n",
       "2        17BP04I  621624             NaN  POINT (462705.715 8344019.122)   \n",
       "3        17BP05I  621625             NaN   POINT (461179.05 8347241.926)   \n",
       "4       RN029663  626981             NaN          POINT (509738 8297777)   \n",
       "5       RN034821  626984             NaN          POINT (514784 8313635)   \n",
       "6       RN029660  626986             NaN  POINT (500047.884 8295266.378)   \n",
       "7       RN029665  626987             NaN          POINT (512860 8302461)   \n",
       "8       RN029653  626988             NaN          POINT (514021 8301501)   \n",
       "9       RN029656  626989             NaN          POINT (504845 8293381)   \n",
       "10      RN029666  626990             NaN          POINT (518194 8307268)   \n",
       "11      RN029662  626991             NaN          POINT (500590 8288080)   \n",
       "12      RN030826  626992             NaN          POINT (501892 8274331)   \n",
       "13       13BP01D  627061             NaN    POINT (473886.62 8333260.73)   \n",
       "14      81010175  627062        Yow Bore          POINT (470932 8351821)   \n",
       "15       17BP06I  627063             NaN  POINT (476482.346 8321899.871)   \n",
       "16      RN039880  627064         17BP07I   POINT (468859.889 8331473.34)   \n",
       "17      RN039888  628981        18BP07-D          POINT (468836 8331457)   \n",
       "18      RN040873  635728            KR08    POINT (520144.76 8306293.88)   \n",
       "19      RN040879  635729           KR21a  POINT (523301.492 8314853.537)   \n",
       "20      RN040880  635730           KR22a  POINT (523640.009 8316422.357)   \n",
       "21      RN040782  635732            KR23  POINT (522411.732 8301368.526)   \n",
       "22      RN040874  635733            KR30   POINT (501830.614 8295403.07)   \n",
       "23      RN040877  635734            KR31  POINT (504915.931 8292360.686)   \n",
       "24      RN040878  635735            KR33  POINT (505309.448 8293856.701)   \n",
       "25      RN040783  635736            KR36  POINT (509392.776 8307934.098)   \n",
       "26      RN040884  635737            KR38  POINT (507769.229 8299897.749)   \n",
       "27      RN040883  635738            KR40  POINT (514309.962 8298828.237)   \n",
       "28      RN040881  635739            KR45  POINT (500051.985 8295681.132)   \n",
       "29      RN040882  635740            KR46  POINT (500053.109 8296644.456)   \n",
       "..           ...     ...             ...                             ...   \n",
       "41      RN039890  635923        18BP01-D          POINT (479026 8334987)   \n",
       "42      RN039169  635957             NaN          POINT (502856 8296555)   \n",
       "43      RN040310  635958             NaN          POINT (507701 8296949)   \n",
       "44      RN040311  635959             NaN          POINT (513882 8298826)   \n",
       "45      RN040315  635960             NaN          POINT (518761 8298429)   \n",
       "46      RN007412  636181             NaN      POINT (505548.7 8292329.3)   \n",
       "47      RN029933  636182             NaN      POINT (533361.5 8319410.2)   \n",
       "48      RN029945  636183             NaN      POINT (520250.6 8296657.3)   \n",
       "49      RN030884  636184             NaN          POINT (499585 8274061)   \n",
       "50      RN030885  636185             NaN      POINT (499613.8 8274026.4)   \n",
       "51      RN038543  636186             NaN          POINT (538158 8333350)   \n",
       "52      RN039870  636187         17BP02I      POINT (468839 8347946.281)   \n",
       "53        FW1mon  636188             NaN          POINT (470862 8268419)   \n",
       "54        10WP39  636189             NaN  POINT (486098.168 8295716.033)   \n",
       "55        10WP42  636190             NaN   POINT (487500.84 8295383.694)   \n",
       "56      80918500  636191      KC10,Ord16          POINT (499481 8278726)   \n",
       "57      80918219  636192           Ord37          POINT (450804 8281036)   \n",
       "58      80918517  636193         WBS1155          POINT (497352 8285299)   \n",
       "59      80918284  636194           Ord24          POINT (499770 8287091)   \n",
       "60      81010136  636195         WBS5080          POINT (497129 8293599)   \n",
       "61      10WP32PB  636196             NaN  POINT (486513.137 8290539.107)   \n",
       "62        10WP46  636197             NaN   POINT (486593.359 8295887.04)   \n",
       "63      80918510  636198            KC13  POINT (495809.481 8277098.459)   \n",
       "64      81070001  636200          10WP36          POINT (481885 8289596)   \n",
       "65      80918511  636201            KC14  POINT (497960.303 8278737.019)   \n",
       "66      80918301  636203           Ord40          POINT (441916 8283743)   \n",
       "67      80918513  636204           KC3PB  POINT (498131.764 8284346.403)   \n",
       "68      80918508  636205            KC11          POINT (497425 8284141)   \n",
       "69          KR58  635749             NaN      POINT (432985.0 8287369.0)   \n",
       "70          IP02  635920             NaN      POINT (441693.0 8289537.0)   \n",
       "\n",
       "    ground_elevation_(mAHD)  Induction_acquired  Gamma_acquired  \\\n",
       "0                    41.750                   1               1   \n",
       "1                   109.525                   1               1   \n",
       "2                    66.474                   1               1   \n",
       "3                    41.333                   1               1   \n",
       "4                    14.936                   1               1   \n",
       "5                    12.281                   1               1   \n",
       "6                    19.217                   1               1   \n",
       "7                    11.873                   1               1   \n",
       "8                    12.904                   1               1   \n",
       "9                    17.650                   1               1   \n",
       "10                    9.266                   1               1   \n",
       "11                   18.952                   1               1   \n",
       "12                   28.793                   1               1   \n",
       "13                   84.040                   1               1   \n",
       "14                    6.308                   1               1   \n",
       "15                   94.617                   1               1   \n",
       "16                   93.167                   1               1   \n",
       "17                   92.860                   1               1   \n",
       "18                    7.519                   1               1   \n",
       "19                    4.575                   1               1   \n",
       "20                    4.364                   1               1   \n",
       "21                   12.030                   1               1   \n",
       "22                   17.506                   1               1   \n",
       "23                   17.913                   1               0   \n",
       "24                   16.494                   1               1   \n",
       "25                   16.490                   1               1   \n",
       "26                   12.462                   1               1   \n",
       "27                   17.673                   1               1   \n",
       "28                   18.799                   1               1   \n",
       "29                   18.357                   1               1   \n",
       "..                      ...                 ...             ...   \n",
       "41                   41.337                   1               1   \n",
       "42                   17.107                   1               1   \n",
       "43                   15.018                   1               1   \n",
       "44                   18.267                   1               1   \n",
       "45                   19.814                   1               1   \n",
       "46                   17.345                   1               1   \n",
       "47                    9.683                   1               1   \n",
       "48                   16.924                   1               1   \n",
       "49                   28.644                   1               1   \n",
       "50                   28.689                   1               1   \n",
       "51                    7.480                   1               1   \n",
       "52                   44.489                   1               1   \n",
       "53                   36.146                   0               1   \n",
       "54                   23.257                   1               1   \n",
       "55                   22.867                   1               1   \n",
       "56                   25.025                   1               1   \n",
       "57                   16.941                   1               1   \n",
       "58                   20.364                   1               1   \n",
       "59                   18.944                   1               1   \n",
       "60                   20.660                   1               1   \n",
       "61                   25.641                   1               1   \n",
       "62                   22.991                   1               1   \n",
       "63                   25.753                   1               1   \n",
       "64                   26.305                   1               1   \n",
       "65                   24.845                   1               1   \n",
       "66                    7.232                   1               1   \n",
       "67                   21.279                   1               1   \n",
       "68                   21.211                   0               1   \n",
       "69                    5.900                   0               0   \n",
       "70                    5.800                   0               0   \n",
       "\n",
       "    Javelin_acquired  Hylogger_chips_acquired  Hylogger_core_acquired  \\\n",
       "0                  1                        0                       0   \n",
       "1                  1                        0                       0   \n",
       "2                  0                        0                       0   \n",
       "3                  0                        0                       0   \n",
       "4                  0                        0                       0   \n",
       "5                  0                        0                       0   \n",
       "6                  0                        0                       0   \n",
       "7                  0                        0                       0   \n",
       "8                  0                        0                       0   \n",
       "9                  0                        0                       0   \n",
       "10                 0                        0                       0   \n",
       "11                 0                        0                       0   \n",
       "12                 0                        0                       0   \n",
       "13                 0                        0                       0   \n",
       "14                 0                        0                       0   \n",
       "15                 1                        0                       0   \n",
       "16                 1                        0                       0   \n",
       "17                 1                        1                       1   \n",
       "18                 1                        0                       1   \n",
       "19                 1                        0                       0   \n",
       "20                 1                        0                       1   \n",
       "21                 1                        1                       0   \n",
       "22                 1                        0                       1   \n",
       "23                 1                        0                       1   \n",
       "24                 1                        0                       1   \n",
       "25                 1                        1                       1   \n",
       "26                 1                        0                       1   \n",
       "27                 1                        0                       1   \n",
       "28                 1                        0                       1   \n",
       "29                 1                        0                       1   \n",
       "..               ...                      ...                     ...   \n",
       "41                 1                        1                       1   \n",
       "42                 0                        0                       0   \n",
       "43                 0                        0                       0   \n",
       "44                 0                        0                       0   \n",
       "45                 0                        0                       0   \n",
       "46                 0                        0                       0   \n",
       "47                 0                        0                       0   \n",
       "48                 0                        0                       0   \n",
       "49                 0                        0                       0   \n",
       "50                 0                        0                       0   \n",
       "51                 0                        0                       0   \n",
       "52                 1                        0                       0   \n",
       "53                 0                        0                       0   \n",
       "54                 0                        0                       0   \n",
       "55                 0                        0                       0   \n",
       "56                 0                        0                       0   \n",
       "57                 0                        0                       0   \n",
       "58                 0                        0                       0   \n",
       "59                 0                        0                       0   \n",
       "60                 0                        0                       0   \n",
       "61                 0                        0                       0   \n",
       "62                 0                        0                       0   \n",
       "63                 0                        0                       0   \n",
       "64                 0                        0                       0   \n",
       "65                 0                        0                       0   \n",
       "66                 0                        0                       0   \n",
       "67                 0                        0                       0   \n",
       "68                 0                        0                       0   \n",
       "69                 1                        0                       1   \n",
       "70                 0                        0                       1   \n",
       "\n",
       "    lithology_description  EC_pH_acquired  SWL_available  \\\n",
       "0                       0               0              1   \n",
       "1                       0               0              1   \n",
       "2                       0               0              1   \n",
       "3                       0               0              1   \n",
       "4                       0               0              1   \n",
       "5                       0               0              1   \n",
       "6                       0               0              1   \n",
       "7                       0               0              1   \n",
       "8                       0               0              1   \n",
       "9                       0               0              1   \n",
       "10                      0               0              1   \n",
       "11                      0               0              1   \n",
       "12                      0               0              1   \n",
       "13                      0               0              1   \n",
       "14                      0               0              0   \n",
       "15                      0               0              1   \n",
       "16                      0               0              1   \n",
       "17                      0               0              1   \n",
       "18                      1               1              1   \n",
       "19                      1               0              1   \n",
       "20                      1               1              1   \n",
       "21                      0               0              1   \n",
       "22                      1               1              1   \n",
       "23                      1               1              1   \n",
       "24                      1               1              1   \n",
       "25                      0               0              1   \n",
       "26                      1               1              1   \n",
       "27                      1               1              1   \n",
       "28                      1               1              1   \n",
       "29                      1               1              1   \n",
       "..                    ...             ...            ...   \n",
       "41                      0               0              1   \n",
       "42                      0               0              1   \n",
       "43                      0               0              1   \n",
       "44                      0               0              1   \n",
       "45                      0               0              1   \n",
       "46                      0               0              1   \n",
       "47                      0               0              1   \n",
       "48                      0               0              0   \n",
       "49                      0               0              1   \n",
       "50                      0               0              1   \n",
       "51                      0               0              1   \n",
       "52                      0               0              1   \n",
       "53                      0               0              1   \n",
       "54                      0               0              1   \n",
       "55                      0               0              1   \n",
       "56                      0               0              1   \n",
       "57                      0               0              1   \n",
       "58                      0               0              1   \n",
       "59                      0               0              1   \n",
       "60                      0               0              1   \n",
       "61                      0               0              1   \n",
       "62                      0               0              1   \n",
       "63                      0               0              1   \n",
       "64                      0               0              1   \n",
       "65                      0               0              1   \n",
       "66                      0               0              1   \n",
       "67                      0               0              1   \n",
       "68                      0               0              1   \n",
       "69                      1               1              1   \n",
       "70                      1               0              0   \n",
       "\n",
       "    Construction_available  MagSus_available  AEM_conductivity_available  \\\n",
       "0                        0                 0                           1   \n",
       "1                        0                 0                           1   \n",
       "2                        0                 0                           1   \n",
       "3                        0                 0                           1   \n",
       "4                        0                 0                           1   \n",
       "5                        0                 0                           1   \n",
       "6                        0                 0                           1   \n",
       "7                        0                 0                           1   \n",
       "8                        0                 0                           1   \n",
       "9                        0                 0                           1   \n",
       "10                       0                 0                           1   \n",
       "11                       0                 0                           1   \n",
       "12                       0                 0                           1   \n",
       "13                       0                 0                           1   \n",
       "14                       0                 0                           1   \n",
       "15                       0                 0                           1   \n",
       "16                       0                 0                           1   \n",
       "17                       1                 0                           1   \n",
       "18                       1                 1                           1   \n",
       "19                       1                 0                           1   \n",
       "20                       1                 1                           1   \n",
       "21                       1                 0                           1   \n",
       "22                       1                 1                           1   \n",
       "23                       1                 1                           1   \n",
       "24                       1                 1                           1   \n",
       "25                       1                 0                           1   \n",
       "26                       1                 1                           1   \n",
       "27                       1                 1                           1   \n",
       "28                       1                 1                           1   \n",
       "29                       1                 1                           1   \n",
       "..                     ...               ...                         ...   \n",
       "41                       1                 0                           1   \n",
       "42                       0                 0                           1   \n",
       "43                       0                 0                           1   \n",
       "44                       0                 0                           1   \n",
       "45                       0                 0                           1   \n",
       "46                       0                 0                           1   \n",
       "47                       0                 0                           1   \n",
       "48                       0                 0                           1   \n",
       "49                       0                 0                           1   \n",
       "50                       0                 0                           1   \n",
       "51                       0                 0                           1   \n",
       "52                       0                 0                           1   \n",
       "53                       0                 0                           1   \n",
       "54                       0                 0                           1   \n",
       "55                       0                 0                           1   \n",
       "56                       0                 0                           1   \n",
       "57                       0                 0                           0   \n",
       "58                       0                 0                           1   \n",
       "59                       0                 0                           1   \n",
       "60                       0                 0                           1   \n",
       "61                       0                 0                           1   \n",
       "62                       0                 0                           1   \n",
       "63                       0                 0                           0   \n",
       "64                       0                 0                           1   \n",
       "65                       0                 0                           1   \n",
       "66                       0                 0                           0   \n",
       "67                       0                 0                           1   \n",
       "68                       0                 0                           1   \n",
       "69                       1                 1                           0   \n",
       "70                       1                 1                           0   \n",
       "\n",
       "       easting     northing  \n",
       "0   478993.383  8335027.204  \n",
       "1   469012.153  8340498.650  \n",
       "2   462705.715  8344019.122  \n",
       "3   461179.050  8347241.926  \n",
       "4   509738.000  8297777.000  \n",
       "5   514784.000  8313635.000  \n",
       "6   500047.884  8295266.378  \n",
       "7   512860.000  8302461.000  \n",
       "8   514021.000  8301501.000  \n",
       "9   504845.000  8293381.000  \n",
       "10  518194.000  8307268.000  \n",
       "11  500590.000  8288080.000  \n",
       "12  501892.000  8274331.000  \n",
       "13  473886.620  8333260.730  \n",
       "14  470932.000  8351821.000  \n",
       "15  476482.346  8321899.871  \n",
       "16  468859.889  8331473.340  \n",
       "17  468836.000  8331457.000  \n",
       "18  520144.760  8306293.880  \n",
       "19  523301.492  8314853.537  \n",
       "20  523640.009  8316422.357  \n",
       "21  522411.732  8301368.526  \n",
       "22  501830.614  8295403.070  \n",
       "23  504915.931  8292360.686  \n",
       "24  505309.448  8293856.701  \n",
       "25  509392.776  8307934.098  \n",
       "26  507769.229  8299897.749  \n",
       "27  514309.962  8298828.237  \n",
       "28  500051.985  8295681.132  \n",
       "29  500053.109  8296644.456  \n",
       "..         ...          ...  \n",
       "41  479026.000  8334987.000  \n",
       "42  502856.000  8296555.000  \n",
       "43  507701.000  8296949.000  \n",
       "44  513882.000  8298826.000  \n",
       "45  518761.000  8298429.000  \n",
       "46  505548.700  8292329.300  \n",
       "47  533361.500  8319410.200  \n",
       "48  520250.600  8296657.300  \n",
       "49  499585.000  8274061.000  \n",
       "50  499613.800  8274026.400  \n",
       "51  538158.000  8333350.000  \n",
       "52  468839.000  8347946.281  \n",
       "53  470862.000  8268419.000  \n",
       "54  486098.168  8295716.033  \n",
       "55  487500.840  8295383.694  \n",
       "56  499481.000  8278726.000  \n",
       "57  450804.000  8281036.000  \n",
       "58  497352.000  8285299.000  \n",
       "59  499770.000  8287091.000  \n",
       "60  497129.000  8293599.000  \n",
       "61  486513.137  8290539.107  \n",
       "62  486593.359  8295887.040  \n",
       "63  495809.481  8277098.459  \n",
       "64  481885.000  8289596.000  \n",
       "65  497960.303  8278737.019  \n",
       "66  441916.000  8283743.000  \n",
       "67  498131.764  8284346.403  \n",
       "68  497425.000  8284141.000  \n",
       "69  432985.000  8287369.000  \n",
       "70  441693.000  8289537.000  \n",
       "\n",
       "[71 rows x 18 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_header"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now that the data has been loaded we write it to the spatialite database\n",
    "\n",
    "# Add header data to a list\n",
    "\n",
    "\n",
    "all_bores = []\n",
    "\n",
    "for index, row in df_header.iterrows():\n",
    "    bore = Boreholes(borehole_id = row['ENO'],\n",
    "                 borehole_name = row['BOREHOLE_NAME'],\n",
    "                 alternative_name = row['ALTERNATE_NAMES'],\n",
    "                 easting = row['easting'],\n",
    "                 northing = row['northing'],\n",
    "                 elevation = row['ground_elevation_(mAHD)'],\n",
    "                 induction = row['Induction_acquired'],\n",
    "                 gamma = row['Gamma_acquired'],\n",
    "                 javelin = row['Javelin_acquired'],\n",
    "                 hylogger_chips = row['Hylogger_chips_acquired'],\n",
    "                 hylogger_core = row['Hylogger_core_acquired'],\n",
    "                 lithology = row['lithology_description'],\n",
    "                 ECpH = row[\"EC_pH_acquired\"],\n",
    "                 swl = row[\"SWL_available\"],\n",
    "                 construction = row[\"Construction_available\"],\n",
    "                 magsus = row['MagSus_available'],\n",
    "                 AEM = row['AEM_conductivity_available'],\n",
    "                 geometry = row['geometry'])\n",
    "    \n",
    "    all_bores.append(bore)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add nmr data to a list\n",
    "\n",
    "all_nmr_data = []\n",
    "\n",
    "for index, row in df_bnmr_data.iterrows():\n",
    "    \n",
    "    nmr_data = Borehole_NMR_data(bNMR_id = index,\n",
    "                            depth = row['Depth_mBGL'],\n",
    "                            totalf = row[\"Total_water_content\"],\n",
    "                            clayf = row[\"Clay_water_content\"],\n",
    "                            capf = row[\"Capillary_water_content\"],\n",
    "                            free = row[\"Free_water_content\"],\n",
    "                            T2 = row[\"T2\"],\n",
    "                            K  = row['Ksdr'],\n",
    "                            borehole_id = row['borehole_id'])\n",
    "    \n",
    "    all_nmr_data.append(nmr_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add induction gamma data to a list\n",
    "\n",
    "all_indgam_data = []\n",
    "\n",
    "for index, row in df_indgam.iterrows():\n",
    "    \n",
    "    # COnductivity will be what ever values is available\n",
    "    \n",
    "    if not pd.isnull(row['INDUCTION_BOREHOLE_COMPENSATED']):\n",
    "        \n",
    "        conductivity = row['INDUCTION_BOREHOLE_COMPENSATED']\n",
    "    \n",
    "    elif not pd.isnull(row['INDUCTION_CALIBRATED']):\n",
    "        \n",
    "        conductivity = row['INDUCTION_CALIBRATED']\n",
    "        \n",
    "    else:\n",
    "        \n",
    "        conductivity = np.nan\n",
    "    \n",
    "    indgam_data = Induction_gamma_data(induction_gamma_id = index,\n",
    "                            depth = row['Depth_mBGL'],\n",
    "                            conductivity = conductivity,\n",
    "                            gamma_calibrated = row['GAMMA_CALIBRATED'],\n",
    "                            K = row[\"K\"],\n",
    "                            U = row[\"U\"],\n",
    "                            Th = row[\"TH\"],\n",
    "                            GR  = row['GR'],\n",
    "                            borehole_id = row['borehole_id'])\n",
    "    \n",
    "    all_indgam_data.append(indgam_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_lithology_data = []\n",
    "\n",
    "for index, row in df_lithology.iterrows():\n",
    "    \n",
    "    lithology_data = Lithology(lithology_id = index,\n",
    "                            depth_from = row['Depth_from'],\n",
    "                            depth_to = row[\"Depth_to\"],\n",
    "                            lithology_type = row['Extra Fields for Oracle: EM1 Lithology Type (eg, soil, muddy sand, sandstone), see lookup tab'],\n",
    "                            lithdescription = row['lithology: eg. Sand, fine; Clay; interbedded sand and silt and clay etc.'],\n",
    "                            clay_frac = row['grain size: clay.1'],\n",
    "                            silt_frac = row['grain size: silt'],\n",
    "                            fsand_frac = row['grain size: very fine - fine'],\n",
    "                            msand_frac = row['grain size: medium'],\n",
    "                            csand_frac = row['grain size: coarse-very coarse'],\n",
    "                            granule_frac = row['grain size: granule'],\n",
    "                            pebble_frac = row['grain size: pebble'],\n",
    "                            sorting = row['sort: Sorting'],\n",
    "                            rounding = row['round: Rounding'],\n",
    "                            weathering = row['wth: Weathering'], \n",
    "                            borehole_id = row['borehole_id'])\n",
    "    \n",
    "    all_lithology_data.append(lithology_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>borehole_id</th>\n",
       "      <th>hole</th>\n",
       "      <th>Depth_from</th>\n",
       "      <th>Depth_to</th>\n",
       "      <th>seq: Interval Sequence Number</th>\n",
       "      <th>Absolute Position: Run</th>\n",
       "      <th>Absolute Position: Sausage</th>\n",
       "      <th>Absolute Position: Length</th>\n",
       "      <th>box: Box Number</th>\n",
       "      <th>...</th>\n",
       "      <th>comments.1: Sedimentary Environment</th>\n",
       "      <th>Extra Fields for Oracle: EM1 Lithology Type (eg, soil, muddy sand, sandstone), see lookup tab</th>\n",
       "      <th>Extra Fields for Oracle: EM1 Proportion (%)</th>\n",
       "      <th>Extra Fields for Oracle: EM2 Lithology Type (eg, soil, muddy sand, sandstone)</th>\n",
       "      <th>Extra Fields for Oracle: EM2 Proportion (%)</th>\n",
       "      <th>Extra Fields for Oracle: Lithology Type Confidence</th>\n",
       "      <th>Extra Fields for Oracle: Other Properties Confidence</th>\n",
       "      <th>Extra Fields for Oracle: Does the colour grade from Dominant to Minor (Y/N)</th>\n",
       "      <th>Extra Fields for Oracle: Requires Manual Entry (Y/N)</th>\n",
       "      <th>Extra Fields for Oracle: Manual Update Comments</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.237</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>aeolian?</td>\n",
       "      <td>soil</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>0.237</td>\n",
       "      <td>0.922</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>aeolian?</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>0.922</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>floodplain</td>\n",
       "      <td>sandy mud</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.866</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>proximal floodplain</td>\n",
       "      <td>muddy sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>2.866</td>\n",
       "      <td>3.841</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>proximal floodplain</td>\n",
       "      <td>muddy sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>3.841</td>\n",
       "      <td>5.000</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>proximal floodplain</td>\n",
       "      <td>muddy sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>6</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>5.000</td>\n",
       "      <td>5.281</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>proximal floodplain</td>\n",
       "      <td>muddy sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>5.281</td>\n",
       "      <td>5.716</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>8</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>5.716</td>\n",
       "      <td>5.921</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>muddy sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>5.921</td>\n",
       "      <td>10.079</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>10.079</td>\n",
       "      <td>10.463</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>gravel bar</td>\n",
       "      <td>gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>10.463</td>\n",
       "      <td>12.559</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>12</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>12.559</td>\n",
       "      <td>13.004</td>\n",
       "      <td>13</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>gravel bar</td>\n",
       "      <td>gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>13.004</td>\n",
       "      <td>13.140</td>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>87</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gravelly sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>14</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>13.140</td>\n",
       "      <td>13.598</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel fill</td>\n",
       "      <td>gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>15</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>13.598</td>\n",
       "      <td>14.885</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel fill</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>16</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>14.885</td>\n",
       "      <td>16.332</td>\n",
       "      <td>17</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel fill</td>\n",
       "      <td>gravelly sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>17</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>16.332</td>\n",
       "      <td>17.352</td>\n",
       "      <td>18</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>debris flow</td>\n",
       "      <td>gravelly sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>18</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>17.352</td>\n",
       "      <td>18.057</td>\n",
       "      <td>19</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel bar</td>\n",
       "      <td>gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>19</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>18.057</td>\n",
       "      <td>19.025</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>gravelly sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>20</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>19.025</td>\n",
       "      <td>22.723</td>\n",
       "      <td>21</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>63</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>21</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>22.723</td>\n",
       "      <td>24.831</td>\n",
       "      <td>22</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>62</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>22</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>24.831</td>\n",
       "      <td>25.457</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>23</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>25.457</td>\n",
       "      <td>26.366</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>24</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>26.366</td>\n",
       "      <td>31.263</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>25</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>31.263</td>\n",
       "      <td>32.150</td>\n",
       "      <td>26</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>26</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>32.150</td>\n",
       "      <td>35.600</td>\n",
       "      <td>27</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>27</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>35.600</td>\n",
       "      <td>35.804</td>\n",
       "      <td>28</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial bar</td>\n",
       "      <td>gravelly sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>28</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>35.804</td>\n",
       "      <td>36.958</td>\n",
       "      <td>29</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>29</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>36.958</td>\n",
       "      <td>37.094</td>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>debris flow</td>\n",
       "      <td>sandy gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>30</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>37.094</td>\n",
       "      <td>37.502</td>\n",
       "      <td>31</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>64</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>31</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>37.502</td>\n",
       "      <td>37.740</td>\n",
       "      <td>32</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>debris flow</td>\n",
       "      <td>sandy gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>32</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>37.740</td>\n",
       "      <td>39.121</td>\n",
       "      <td>33</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>fluvial channel</td>\n",
       "      <td>sand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>33</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>39.121</td>\n",
       "      <td>40.287</td>\n",
       "      <td>34</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>debris flow</td>\n",
       "      <td>sandy gravel</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>34</td>\n",
       "      <td>635728</td>\n",
       "      <td>KR08</td>\n",
       "      <td>40.287</td>\n",
       "      <td>42.000</td>\n",
       "      <td>35</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>80</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>sandstone basement</td>\n",
       "      <td>sandstone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>H</td>\n",
       "      <td>H</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35 rows × 69 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  borehole_id  hole  Depth_from  Depth_to  \\\n",
       "10           0       635728  KR08       0.000     0.237   \n",
       "11           1       635728  KR08       0.237     0.922   \n",
       "12           2       635728  KR08       0.922     2.000   \n",
       "13           3       635728  KR08       2.000     2.866   \n",
       "14           4       635728  KR08       2.866     3.841   \n",
       "15           5       635728  KR08       3.841     5.000   \n",
       "16           6       635728  KR08       5.000     5.281   \n",
       "17           7       635728  KR08       5.281     5.716   \n",
       "18           8       635728  KR08       5.716     5.921   \n",
       "19           9       635728  KR08       5.921    10.079   \n",
       "20          10       635728  KR08      10.079    10.463   \n",
       "21          11       635728  KR08      10.463    12.559   \n",
       "22          12       635728  KR08      12.559    13.004   \n",
       "23          13       635728  KR08      13.004    13.140   \n",
       "24          14       635728  KR08      13.140    13.598   \n",
       "25          15       635728  KR08      13.598    14.885   \n",
       "26          16       635728  KR08      14.885    16.332   \n",
       "27          17       635728  KR08      16.332    17.352   \n",
       "28          18       635728  KR08      17.352    18.057   \n",
       "29          19       635728  KR08      18.057    19.025   \n",
       "30          20       635728  KR08      19.025    22.723   \n",
       "31          21       635728  KR08      22.723    24.831   \n",
       "32          22       635728  KR08      24.831    25.457   \n",
       "33          23       635728  KR08      25.457    26.366   \n",
       "34          24       635728  KR08      26.366    31.263   \n",
       "35          25       635728  KR08      31.263    32.150   \n",
       "36          26       635728  KR08      32.150    35.600   \n",
       "37          27       635728  KR08      35.600    35.804   \n",
       "38          28       635728  KR08      35.804    36.958   \n",
       "39          29       635728  KR08      36.958    37.094   \n",
       "40          30       635728  KR08      37.094    37.502   \n",
       "41          31       635728  KR08      37.502    37.740   \n",
       "42          32       635728  KR08      37.740    39.121   \n",
       "43          33       635728  KR08      39.121    40.287   \n",
       "44          34       635728  KR08      40.287    42.000   \n",
       "\n",
       "    seq: Interval Sequence Number  Absolute Position: Run  \\\n",
       "10                              1                       1   \n",
       "11                              2                       1   \n",
       "12                              3                       2   \n",
       "13                              4                       2   \n",
       "14                              5                       2   \n",
       "15                              6                       3   \n",
       "16                              7                       3   \n",
       "17                              8                       3   \n",
       "18                              9                       3   \n",
       "19                             10                       3   \n",
       "20                             11                       3   \n",
       "21                             12                       4   \n",
       "22                             13                       4   \n",
       "23                             14                       4   \n",
       "24                             15                       4   \n",
       "25                             16                       4   \n",
       "26                             17                       4   \n",
       "27                             18                       5   \n",
       "28                             19                       5   \n",
       "29                             20                       5   \n",
       "30                             21                       5   \n",
       "31                             22                       6   \n",
       "32                             23                       6   \n",
       "33                             24                       6   \n",
       "34                             25                       7   \n",
       "35                             26                       7   \n",
       "36                             27                       8   \n",
       "37                             28                       8   \n",
       "38                             29                       8   \n",
       "39                             30                       8   \n",
       "40                             31                       8   \n",
       "41                             32                       8   \n",
       "42                             33                       8   \n",
       "43                             34                       8   \n",
       "44                             35                       9   \n",
       "\n",
       "   Absolute Position: Sausage  Absolute Position: Length box: Box Number  \\\n",
       "10                          1                         26             NaN   \n",
       "11                          2                         22             NaN   \n",
       "12                          1                          0             NaN   \n",
       "13                          2                          0             NaN   \n",
       "14                          2                         80             NaN   \n",
       "15                          1                          0             NaN   \n",
       "16                          1                         22             NaN   \n",
       "17                          1                         56             NaN   \n",
       "18                          1                         72             NaN   \n",
       "19                          5                         74             NaN   \n",
       "20                          6                         22             NaN   \n",
       "21                          2                         40             NaN   \n",
       "22                          2                         76             NaN   \n",
       "23                          2                         87             NaN   \n",
       "24                          3                         36             NaN   \n",
       "25                          4                         54             NaN   \n",
       "26                          6                         27             NaN   \n",
       "27                          1                         28             NaN   \n",
       "28                          2                          0             NaN   \n",
       "29                          3                          0             NaN   \n",
       "30                          6                         63             NaN   \n",
       "31                          2                         62             NaN   \n",
       "32                          3                         26             NaN   \n",
       "33                          4                         20             NaN   \n",
       "34                          3                         28             NaN   \n",
       "35                          4                         23             NaN   \n",
       "36                          1                         53             NaN   \n",
       "37                          2                          0             NaN   \n",
       "38                          3                         16             NaN   \n",
       "39                          3                         28             NaN   \n",
       "40                          3                         64             NaN   \n",
       "41                          4                          0             NaN   \n",
       "42                          5                         20             NaN   \n",
       "43                          6                         24             NaN   \n",
       "44                          1                         80             NaN   \n",
       "\n",
       "                         ...                        \\\n",
       "10                       ...                         \n",
       "11                       ...                         \n",
       "12                       ...                         \n",
       "13                       ...                         \n",
       "14                       ...                         \n",
       "15                       ...                         \n",
       "16                       ...                         \n",
       "17                       ...                         \n",
       "18                       ...                         \n",
       "19                       ...                         \n",
       "20                       ...                         \n",
       "21                       ...                         \n",
       "22                       ...                         \n",
       "23                       ...                         \n",
       "24                       ...                         \n",
       "25                       ...                         \n",
       "26                       ...                         \n",
       "27                       ...                         \n",
       "28                       ...                         \n",
       "29                       ...                         \n",
       "30                       ...                         \n",
       "31                       ...                         \n",
       "32                       ...                         \n",
       "33                       ...                         \n",
       "34                       ...                         \n",
       "35                       ...                         \n",
       "36                       ...                         \n",
       "37                       ...                         \n",
       "38                       ...                         \n",
       "39                       ...                         \n",
       "40                       ...                         \n",
       "41                       ...                         \n",
       "42                       ...                         \n",
       "43                       ...                         \n",
       "44                       ...                         \n",
       "\n",
       "   comments.1: Sedimentary Environment  \\\n",
       "10                            aeolian?   \n",
       "11                            aeolian?   \n",
       "12                          floodplain   \n",
       "13                 proximal floodplain   \n",
       "14                 proximal floodplain   \n",
       "15                 proximal floodplain   \n",
       "16                 proximal floodplain   \n",
       "17                     fluvial channel   \n",
       "18                     fluvial channel   \n",
       "19                     fluvial channel   \n",
       "20                          gravel bar   \n",
       "21                     fluvial channel   \n",
       "22                          gravel bar   \n",
       "23                                 NaN   \n",
       "24                fluvial channel fill   \n",
       "25                fluvial channel fill   \n",
       "26                fluvial channel fill   \n",
       "27                         debris flow   \n",
       "28                 fluvial channel bar   \n",
       "29                     fluvial channel   \n",
       "30                     fluvial channel   \n",
       "31                     fluvial channel   \n",
       "32                     fluvial channel   \n",
       "33                     fluvial channel   \n",
       "34                     fluvial channel   \n",
       "35                     fluvial channel   \n",
       "36                     fluvial channel   \n",
       "37                         fluvial bar   \n",
       "38                     fluvial channel   \n",
       "39                         debris flow   \n",
       "40                     fluvial channel   \n",
       "41                         debris flow   \n",
       "42                     fluvial channel   \n",
       "43                         debris flow   \n",
       "44                  sandstone basement   \n",
       "\n",
       "   Extra Fields for Oracle: EM1 Lithology Type (eg, soil, muddy sand, sandstone), see lookup tab  \\\n",
       "10                                               soil                                              \n",
       "11                                               sand                                              \n",
       "12                                          sandy mud                                              \n",
       "13                                         muddy sand                                              \n",
       "14                                         muddy sand                                              \n",
       "15                                         muddy sand                                              \n",
       "16                                         muddy sand                                              \n",
       "17                                               sand                                              \n",
       "18                                         muddy sand                                              \n",
       "19                                               sand                                              \n",
       "20                                             gravel                                              \n",
       "21                                               sand                                              \n",
       "22                                             gravel                                              \n",
       "23                                      gravelly sand                                              \n",
       "24                                             gravel                                              \n",
       "25                                               sand                                              \n",
       "26                                      gravelly sand                                              \n",
       "27                                      gravelly sand                                              \n",
       "28                                             gravel                                              \n",
       "29                                      gravelly sand                                              \n",
       "30                                               sand                                              \n",
       "31                                               sand                                              \n",
       "32                                               sand                                              \n",
       "33                                               sand                                              \n",
       "34                                               sand                                              \n",
       "35                                               sand                                              \n",
       "36                                               sand                                              \n",
       "37                                      gravelly sand                                              \n",
       "38                                               sand                                              \n",
       "39                                       sandy gravel                                              \n",
       "40                                               sand                                              \n",
       "41                                       sandy gravel                                              \n",
       "42                                               sand                                              \n",
       "43                                       sandy gravel                                              \n",
       "44                                          sandstone                                              \n",
       "\n",
       "   Extra Fields for Oracle: EM1 Proportion (%)  \\\n",
       "10                                         NaN   \n",
       "11                                         NaN   \n",
       "12                                         NaN   \n",
       "13                                         NaN   \n",
       "14                                         NaN   \n",
       "15                                         NaN   \n",
       "16                                         NaN   \n",
       "17                                         NaN   \n",
       "18                                         NaN   \n",
       "19                                         NaN   \n",
       "20                                         NaN   \n",
       "21                                         NaN   \n",
       "22                                         NaN   \n",
       "23                                         NaN   \n",
       "24                                         NaN   \n",
       "25                                         NaN   \n",
       "26                                         NaN   \n",
       "27                                         NaN   \n",
       "28                                         NaN   \n",
       "29                                         NaN   \n",
       "30                                         NaN   \n",
       "31                                         NaN   \n",
       "32                                         NaN   \n",
       "33                                         NaN   \n",
       "34                                         NaN   \n",
       "35                                         NaN   \n",
       "36                                         NaN   \n",
       "37                                         NaN   \n",
       "38                                         NaN   \n",
       "39                                         NaN   \n",
       "40                                         NaN   \n",
       "41                                         NaN   \n",
       "42                                         NaN   \n",
       "43                                         NaN   \n",
       "44                                         NaN   \n",
       "\n",
       "   Extra Fields for Oracle: EM2 Lithology Type (eg, soil, muddy sand, sandstone)  \\\n",
       "10                                                NaN                              \n",
       "11                                                NaN                              \n",
       "12                                                NaN                              \n",
       "13                                                NaN                              \n",
       "14                                                NaN                              \n",
       "15                                                NaN                              \n",
       "16                                                NaN                              \n",
       "17                                                NaN                              \n",
       "18                                                NaN                              \n",
       "19                                                NaN                              \n",
       "20                                                NaN                              \n",
       "21                                                NaN                              \n",
       "22                                                NaN                              \n",
       "23                                                NaN                              \n",
       "24                                                NaN                              \n",
       "25                                                NaN                              \n",
       "26                                                NaN                              \n",
       "27                                                NaN                              \n",
       "28                                                NaN                              \n",
       "29                                                NaN                              \n",
       "30                                                NaN                              \n",
       "31                                                NaN                              \n",
       "32                                                NaN                              \n",
       "33                                                NaN                              \n",
       "34                                                NaN                              \n",
       "35                                                NaN                              \n",
       "36                                                NaN                              \n",
       "37                                                NaN                              \n",
       "38                                                NaN                              \n",
       "39                                                NaN                              \n",
       "40                                                NaN                              \n",
       "41                                                NaN                              \n",
       "42                                                NaN                              \n",
       "43                                                NaN                              \n",
       "44                                                NaN                              \n",
       "\n",
       "   Extra Fields for Oracle: EM2 Proportion (%)  \\\n",
       "10                                         NaN   \n",
       "11                                         NaN   \n",
       "12                                         NaN   \n",
       "13                                         NaN   \n",
       "14                                         NaN   \n",
       "15                                         NaN   \n",
       "16                                         NaN   \n",
       "17                                         NaN   \n",
       "18                                         NaN   \n",
       "19                                         NaN   \n",
       "20                                         NaN   \n",
       "21                                         NaN   \n",
       "22                                         NaN   \n",
       "23                                         NaN   \n",
       "24                                         NaN   \n",
       "25                                         NaN   \n",
       "26                                         NaN   \n",
       "27                                         NaN   \n",
       "28                                         NaN   \n",
       "29                                         NaN   \n",
       "30                                         NaN   \n",
       "31                                         NaN   \n",
       "32                                         NaN   \n",
       "33                                         NaN   \n",
       "34                                         NaN   \n",
       "35                                         NaN   \n",
       "36                                         NaN   \n",
       "37                                         NaN   \n",
       "38                                         NaN   \n",
       "39                                         NaN   \n",
       "40                                         NaN   \n",
       "41                                         NaN   \n",
       "42                                         NaN   \n",
       "43                                         NaN   \n",
       "44                                         NaN   \n",
       "\n",
       "   Extra Fields for Oracle: Lithology Type Confidence  \\\n",
       "10                                                  H   \n",
       "11                                                  H   \n",
       "12                                                  H   \n",
       "13                                                  H   \n",
       "14                                                  H   \n",
       "15                                                  H   \n",
       "16                                                  H   \n",
       "17                                                  H   \n",
       "18                                                  H   \n",
       "19                                                  H   \n",
       "20                                                  H   \n",
       "21                                                  H   \n",
       "22                                                  H   \n",
       "23                                                  H   \n",
       "24                                                  H   \n",
       "25                                                  H   \n",
       "26                                                  H   \n",
       "27                                                  H   \n",
       "28                                                  H   \n",
       "29                                                  H   \n",
       "30                                                  H   \n",
       "31                                                  H   \n",
       "32                                                  H   \n",
       "33                                                  H   \n",
       "34                                                  H   \n",
       "35                                                  H   \n",
       "36                                                  H   \n",
       "37                                                  H   \n",
       "38                                                  H   \n",
       "39                                                  H   \n",
       "40                                                  H   \n",
       "41                                                  H   \n",
       "42                                                  H   \n",
       "43                                                  H   \n",
       "44                                                  H   \n",
       "\n",
       "   Extra Fields for Oracle: Other Properties Confidence  \\\n",
       "10                                                  H     \n",
       "11                                                  H     \n",
       "12                                                  H     \n",
       "13                                                  H     \n",
       "14                                                  H     \n",
       "15                                                  H     \n",
       "16                                                  H     \n",
       "17                                                  H     \n",
       "18                                                  H     \n",
       "19                                                  H     \n",
       "20                                                  H     \n",
       "21                                                  H     \n",
       "22                                                  H     \n",
       "23                                                  H     \n",
       "24                                                  H     \n",
       "25                                                  H     \n",
       "26                                                  H     \n",
       "27                                                  H     \n",
       "28                                                  H     \n",
       "29                                                  H     \n",
       "30                                                  H     \n",
       "31                                                  H     \n",
       "32                                                  H     \n",
       "33                                                  H     \n",
       "34                                                  H     \n",
       "35                                                  H     \n",
       "36                                                  H     \n",
       "37                                                  H     \n",
       "38                                                  H     \n",
       "39                                                  H     \n",
       "40                                                  H     \n",
       "41                                                  H     \n",
       "42                                                  H     \n",
       "43                                                  H     \n",
       "44                                                  H     \n",
       "\n",
       "   Extra Fields for Oracle: Does the colour grade from Dominant to Minor (Y/N)  \\\n",
       "10                                                NaN                            \n",
       "11                                                NaN                            \n",
       "12                                                NaN                            \n",
       "13                                                NaN                            \n",
       "14                                                NaN                            \n",
       "15                                                NaN                            \n",
       "16                                                NaN                            \n",
       "17                                                NaN                            \n",
       "18                                                NaN                            \n",
       "19                                                NaN                            \n",
       "20                                                NaN                            \n",
       "21                                                NaN                            \n",
       "22                                                NaN                            \n",
       "23                                                NaN                            \n",
       "24                                                NaN                            \n",
       "25                                                NaN                            \n",
       "26                                                NaN                            \n",
       "27                                                NaN                            \n",
       "28                                                NaN                            \n",
       "29                                                NaN                            \n",
       "30                                                NaN                            \n",
       "31                                                NaN                            \n",
       "32                                                NaN                            \n",
       "33                                                NaN                            \n",
       "34                                                NaN                            \n",
       "35                                                NaN                            \n",
       "36                                                NaN                            \n",
       "37                                                NaN                            \n",
       "38                                                NaN                            \n",
       "39                                                NaN                            \n",
       "40                                                NaN                            \n",
       "41                                                NaN                            \n",
       "42                                                NaN                            \n",
       "43                                                NaN                            \n",
       "44                                                NaN                            \n",
       "\n",
       "   Extra Fields for Oracle: Requires Manual Entry (Y/N)  \\\n",
       "10                                                NaN     \n",
       "11                                                NaN     \n",
       "12                                                NaN     \n",
       "13                                                NaN     \n",
       "14                                                NaN     \n",
       "15                                                NaN     \n",
       "16                                                NaN     \n",
       "17                                                NaN     \n",
       "18                                                NaN     \n",
       "19                                                NaN     \n",
       "20                                                NaN     \n",
       "21                                                NaN     \n",
       "22                                                NaN     \n",
       "23                                                NaN     \n",
       "24                                                NaN     \n",
       "25                                                NaN     \n",
       "26                                                NaN     \n",
       "27                                                NaN     \n",
       "28                                                NaN     \n",
       "29                                                NaN     \n",
       "30                                                NaN     \n",
       "31                                                NaN     \n",
       "32                                                NaN     \n",
       "33                                                NaN     \n",
       "34                                                NaN     \n",
       "35                                                NaN     \n",
       "36                                                NaN     \n",
       "37                                                NaN     \n",
       "38                                                NaN     \n",
       "39                                                NaN     \n",
       "40                                                NaN     \n",
       "41                                                NaN     \n",
       "42                                                NaN     \n",
       "43                                                NaN     \n",
       "44                                                NaN     \n",
       "\n",
       "   Extra Fields for Oracle: Manual Update Comments  \n",
       "10                                             NaN  \n",
       "11                                             NaN  \n",
       "12                                             NaN  \n",
       "13                                             NaN  \n",
       "14                                             NaN  \n",
       "15                                             NaN  \n",
       "16                                             NaN  \n",
       "17                                             NaN  \n",
       "18                                             NaN  \n",
       "19                                             NaN  \n",
       "20                                             NaN  \n",
       "21                                             NaN  \n",
       "22                                             NaN  \n",
       "23                                             NaN  \n",
       "24                                             NaN  \n",
       "25                                             NaN  \n",
       "26                                             NaN  \n",
       "27                                             NaN  \n",
       "28                                             NaN  \n",
       "29                                             NaN  \n",
       "30                                             NaN  \n",
       "31                                             NaN  \n",
       "32                                             NaN  \n",
       "33                                             NaN  \n",
       "34                                             NaN  \n",
       "35                                             NaN  \n",
       "36                                             NaN  \n",
       "37                                             NaN  \n",
       "38                                             NaN  \n",
       "39                                             NaN  \n",
       "40                                             NaN  \n",
       "41                                             NaN  \n",
       "42                                             NaN  \n",
       "43                                             NaN  \n",
       "44                                             NaN  \n",
       "\n",
       "[35 rows x 69 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_lithology[df_lithology['borehole_id'] == 635728]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_EC_pH_data = []\n",
    "\n",
    "for index, row in df_ECpH.iterrows():\n",
    "    \n",
    "    ECpH_data = EC_pH(EC_pH_id = index,\n",
    "                            depth = row['Depth'],\n",
    "                            EC = row[\"EC Value\"],\n",
    "                            pH = row['pH'],\n",
    "                            borehole_id = row['Borehole_eno'])\n",
    "    \n",
    "    \n",
    "    all_EC_pH_data.append(ECpH_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_swl_data = []\n",
    "\n",
    "for index, row in df_swl.iterrows():\n",
    "    \n",
    "    swl_data = SWL(SWL_id = index,\n",
    "                    depth = row['SWL_m'],\n",
    "                    date = row[\"Date Measured\"],\n",
    "                    Measurer = row['Who_Measured'],\n",
    "                    borehole_id = row['ENO'])\n",
    "    \n",
    "    \n",
    "    all_swl_data.append(swl_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_construction_data = []\n",
    "\n",
    "for index, row in df_const.iterrows():\n",
    "    \n",
    "    construction_data = Construction(construction_id = index,\n",
    "                        depth_from = row[\"Depth_from\"],\n",
    "                        depth_to = row[\"Depth_to\"],\n",
    "                        Construction_name = row[\"Construction_name\"],\n",
    "                        Construction_type = row['Construction_type'],\n",
    "                        Construction_materials =row['Construction_materials'],\n",
    "                        Internal_diameter = row[\"Internal_diameter\"],\n",
    "                        Property = row[\"Property\"],\n",
    "                        Property_size = row['Property_size'],\n",
    "                        borehole_id = row['ENO'])\n",
    "    \n",
    "    \n",
    "    all_construction_data.append(construction_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_magsus_data = []\n",
    "\n",
    "for index, row in df_magsus.iterrows():\n",
    "    \n",
    "    magsus_data = MagSus(magsus_id = index,\n",
    "                    depth = row['Sample_Depth_(m)'],\n",
    "                    magsus = row['Mag_sus_(unitless)'],\n",
    "                    borehole_id = row['Borehole_eno'])\n",
    "    \n",
    "    \n",
    "    all_magsus_data.append(magsus_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_aem_data = []\n",
    "\n",
    "for index, row in df_aem.iterrows():\n",
    "    \n",
    "    aem_data = AEM_conductivity(bulk_conductivity_id = index,\n",
    "                    depth_from = row['Depth_from'],\n",
    "                    depth_to = row['Depth_to'],\n",
    "                    conductivity = row['conductivity'],\n",
    "                    borehole_id = row['borehole_id'])\n",
    "    \n",
    "    \n",
    "    all_aem_data.append(aem_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlalchemy.orm import sessionmaker\n",
    "Session = sessionmaker(bind=engine)\n",
    "session = Session()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "ename": "IntegrityError",
     "evalue": "(sqlite3.IntegrityError) borehole.geom violates Geometry constraint [geom-type or SRID not allowed] [SQL: 'INSERT INTO borehole (borehole_id, \"Borehole_name\", \"Alternative_name\", \"Easting\", \"Northing\", \"Ground_elevation_mAHD\", \"Induction_acquired\", \"Gamma_acquired\", \"Javelin_acquired\", \"Hylogger_acquired_on_core\", \"Hylogger_acquired_on_chips\", \"Lithology_available\", \"EC_pH_acquired\", \"SWL_available\", \"Construction_available\", \"MagSus_available\", \"AEM_conductivity_available\", geometry) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)'] [parameters: ((621622, '17BP01I', nan, 478993.383, 8335027.204, 41.75, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (478993.383 8335027.204)'), (621623, '17BP03I', nan, 469012.153, 8340498.65, 109.525, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (469012.153 8340498.65)'), (621624, '17BP04I', nan, 462705.715, 8344019.122, 66.47399999999999, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (462705.715 8344019.122)'), (621625, '17BP05I', nan, 461179.05, 8347241.926, 41.333, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (461179.05 8347241.926)'), (626981, 'RN029663', nan, 509738.0, 8297777.0, 14.936, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (509738 8297777)'), (626984, 'RN034821', nan, 514784.0, 8313635.0, 12.280999999999999, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (514784 8313635)'), (626986, 'RN029660', nan, 500047.884, 8295266.378, 19.217, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (500047.884 8295266.378)'), (626987, 'RN029665', nan, 512860.0, 8302461.0, 11.873, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (512860 8302461)')  ... displaying 10 of 71 total bound parameter sets ...  (635749, 'KR58', nan, 432985.0, 8287369.0, 5.9, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 'POINT (432985.0 8287369.0)'), (635920, 'IP02', nan, 441693.0, 8289537.0, 5.8, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 'POINT (441693.0 8289537.0)'))] (Background on this error at: http://sqlalche.me/e/gkpj)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIntegrityError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1169\u001b[0m                         \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1170\u001b[1;33m                         context)\n\u001b[0m\u001b[0;32m   1171\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mparameters\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mno_parameters\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\default.py\u001b[0m in \u001b[0;36mdo_executemany\u001b[1;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[0;32m    505\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdo_executemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 506\u001b[1;33m         \u001b[0mcursor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecutemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    507\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIntegrityError\u001b[0m: borehole.geom violates Geometry constraint [geom-type or SRID not allowed]",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mIntegrityError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-43-ac2c522d64ae>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0msession\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36mcommit\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    941\u001b[0m                 \u001b[1;32mraise\u001b[0m \u001b[0msa_exc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInvalidRequestError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"No transaction is begun.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    942\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 943\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtransaction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcommit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    944\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    945\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mprepare\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36mcommit\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    465\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_assert_active\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprepared_ok\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    466\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_state\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mPREPARED\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 467\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_prepare_impl\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    468\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    469\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_parent\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnested\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36m_prepare_impl\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    445\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msession\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_is_clean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    446\u001b[0m                     \u001b[1;32mbreak\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 447\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msession\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    448\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    449\u001b[0m                 raise exc.FlushError(\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36mflush\u001b[1;34m(self, objects)\u001b[0m\n\u001b[0;32m   2252\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2253\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_flushing\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2254\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_flush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobjects\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2255\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2256\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_flushing\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36m_flush\u001b[1;34m(self, objects)\u001b[0m\n\u001b[0;32m   2378\u001b[0m         \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2379\u001b[0m             \u001b[1;32mwith\u001b[0m \u001b[0mutil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msafe_reraise\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2380\u001b[1;33m                 \u001b[0mtransaction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrollback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_capture_exception\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2381\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2382\u001b[0m     def bulk_save_objects(\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\util\\langhelpers.py\u001b[0m in \u001b[0;36m__exit__\u001b[1;34m(self, type_, value, traceback)\u001b[0m\n\u001b[0;32m     64\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exc_info\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m   \u001b[1;31m# remove potential circular references\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     65\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwarn_only\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 66\u001b[1;33m                 \u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreraise\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexc_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_value\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_tb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     67\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     68\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpy3k\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exc_info\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_exc_info\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\util\\compat.py\u001b[0m in \u001b[0;36mreraise\u001b[1;34m(tp, value, tb, cause)\u001b[0m\n\u001b[0;32m    247\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    248\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 249\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    250\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    251\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\session.py\u001b[0m in \u001b[0;36m_flush\u001b[1;34m(self, objects)\u001b[0m\n\u001b[0;32m   2342\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_warn_on_events\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2343\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2344\u001b[1;33m                 \u001b[0mflush_context\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2345\u001b[0m             \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2346\u001b[0m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_warn_on_events\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\unitofwork.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    389\u001b[0m                     \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdependencies\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    390\u001b[0m                     postsort_actions):\n\u001b[1;32m--> 391\u001b[1;33m                 \u001b[0mrec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    392\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    393\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mfinalize_flush_changes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\unitofwork.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, uow)\u001b[0m\n\u001b[0;32m    554\u001b[0m                              uow.states_for_mapper_hierarchy(\n\u001b[0;32m    555\u001b[0m                                  self.mapper, False, False),\n\u001b[1;32m--> 556\u001b[1;33m                              \u001b[0muow\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    557\u001b[0m                              )\n\u001b[0;32m    558\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\persistence.py\u001b[0m in \u001b[0;36msave_obj\u001b[1;34m(base_mapper, states, uowtransaction, single)\u001b[0m\n\u001b[0;32m    179\u001b[0m         _emit_insert_statements(base_mapper, uowtransaction,\n\u001b[0;32m    180\u001b[0m                                 \u001b[0mcached_connections\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 181\u001b[1;33m                                 mapper, table, insert)\n\u001b[0m\u001b[0;32m    182\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    183\u001b[0m     _finalize_insert_update_commands(\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\orm\\persistence.py\u001b[0m in \u001b[0;36m_emit_insert_statements\u001b[1;34m(base_mapper, uowtransaction, cached_connections, mapper, table, insert, bookkeeping)\u001b[0m\n\u001b[0;32m    828\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    829\u001b[0m             \u001b[0mc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcached_connections\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mconnection\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0;31m\\\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 830\u001b[1;33m                 \u001b[0mexecute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    831\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    832\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mbookkeeping\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36mexecute\u001b[1;34m(self, object, *multiparams, **params)\u001b[0m\n\u001b[0;32m    946\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    947\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 948\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    949\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    950\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_execute_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\sql\\elements.py\u001b[0m in \u001b[0;36m_execute_on_connection\u001b[1;34m(self, connection, multiparams, params)\u001b[0m\n\u001b[0;32m    267\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_execute_on_connection\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    268\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msupports_execution\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 269\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mconnection\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_execute_clauseelement\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmultiparams\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparams\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    270\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    271\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mObjectNotExecutableError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_clauseelement\u001b[1;34m(self, elem, multiparams, params)\u001b[0m\n\u001b[0;32m   1058\u001b[0m             \u001b[0mcompiled_sql\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1059\u001b[0m             \u001b[0mdistilled_params\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1060\u001b[1;33m             \u001b[0mcompiled_sql\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdistilled_params\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1061\u001b[0m         )\n\u001b[0;32m   1062\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1198\u001b[0m                 \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1199\u001b[0m                 \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1200\u001b[1;33m                 context)\n\u001b[0m\u001b[0;32m   1201\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1202\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_handle_dbapi_exception\u001b[1;34m(self, e, statement, parameters, cursor, context)\u001b[0m\n\u001b[0;32m   1411\u001b[0m                 util.raise_from_cause(\n\u001b[0;32m   1412\u001b[0m                     \u001b[0msqlalchemy_exception\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1413\u001b[1;33m                     \u001b[0mexc_info\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1414\u001b[0m                 )\n\u001b[0;32m   1415\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\util\\compat.py\u001b[0m in \u001b[0;36mraise_from_cause\u001b[1;34m(exception, exc_info)\u001b[0m\n\u001b[0;32m    263\u001b[0m     \u001b[0mexc_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_value\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexc_tb\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexc_info\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    264\u001b[0m     \u001b[0mcause\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mexc_value\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mexception\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 265\u001b[1;33m     \u001b[0mreraise\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mexception\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mexception\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mexc_tb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcause\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mcause\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    266\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    267\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mpy3k\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\util\\compat.py\u001b[0m in \u001b[0;36mreraise\u001b[1;34m(tp, value, tb, cause)\u001b[0m\n\u001b[0;32m    246\u001b[0m             \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__cause__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcause\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    247\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 248\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    249\u001b[0m         \u001b[1;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    250\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\base.py\u001b[0m in \u001b[0;36m_execute_context\u001b[1;34m(self, dialect, constructor, statement, parameters, *args)\u001b[0m\n\u001b[0;32m   1168\u001b[0m                         \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1169\u001b[0m                         \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1170\u001b[1;33m                         context)\n\u001b[0m\u001b[0;32m   1171\u001b[0m             \u001b[1;32melif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mparameters\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mno_parameters\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1172\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdialect\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_events\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\sqlalchemy\\engine\\default.py\u001b[0m in \u001b[0;36mdo_executemany\u001b[1;34m(self, cursor, statement, parameters, context)\u001b[0m\n\u001b[0;32m    504\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    505\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdo_executemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 506\u001b[1;33m         \u001b[0mcursor\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mexecutemany\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    507\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    508\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdo_execute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcursor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatement\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparameters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcontext\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIntegrityError\u001b[0m: (sqlite3.IntegrityError) borehole.geom violates Geometry constraint [geom-type or SRID not allowed] [SQL: 'INSERT INTO borehole (borehole_id, \"Borehole_name\", \"Alternative_name\", \"Easting\", \"Northing\", \"Ground_elevation_mAHD\", \"Induction_acquired\", \"Gamma_acquired\", \"Javelin_acquired\", \"Hylogger_acquired_on_core\", \"Hylogger_acquired_on_chips\", \"Lithology_available\", \"EC_pH_acquired\", \"SWL_available\", \"Construction_available\", \"MagSus_available\", \"AEM_conductivity_available\", geometry) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)'] [parameters: ((621622, '17BP01I', nan, 478993.383, 8335027.204, 41.75, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (478993.383 8335027.204)'), (621623, '17BP03I', nan, 469012.153, 8340498.65, 109.525, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (469012.153 8340498.65)'), (621624, '17BP04I', nan, 462705.715, 8344019.122, 66.47399999999999, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (462705.715 8344019.122)'), (621625, '17BP05I', nan, 461179.05, 8347241.926, 41.333, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (461179.05 8347241.926)'), (626981, 'RN029663', nan, 509738.0, 8297777.0, 14.936, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (509738 8297777)'), (626984, 'RN034821', nan, 514784.0, 8313635.0, 12.280999999999999, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (514784 8313635)'), (626986, 'RN029660', nan, 500047.884, 8295266.378, 19.217, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (500047.884 8295266.378)'), (626987, 'RN029665', nan, 512860.0, 8302461.0, 11.873, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 'POINT (512860 8302461)')  ... displaying 10 of 71 total bound parameter sets ...  (635749, 'KR58', nan, 432985.0, 8287369.0, 5.9, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 'POINT (432985.0 8287369.0)'), (635920, 'IP02', nan, 441693.0, 8289537.0, 5.8, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 'POINT (441693.0 8289537.0)'))] (Background on this error at: http://sqlalche.me/e/gkpj)"
     ]
    }
   ],
   "source": [
    "session.add_all(all_bores)\n",
    "session.add_all(all_nmr_data)\n",
    "session.add_all(all_indgam_data)\n",
    "session.add_all(all_lithology_data)\n",
    "session.add_all(all_EC_pH_data)\n",
    "session.add_all(all_swl_data)\n",
    "session.add_all(all_construction_data)\n",
    "session.add_all(all_magsus_data)\n",
    "session.add_all(all_aem_data)\n",
    "\n",
    "\n",
    "session.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create the spatialite table\n",
    "\n",
    "# add a Spatialite geometry column called 'geom' to the table, using ESPG 28352,\n",
    "# data type POLYGON and 2 dimensions (x, y)\n",
    "engine.execute(\"SELECT AddGeometryColumn('borehole', 'geom', 28352, 'POINT', 'XY', 1);\")\n",
    "\n",
    "# update the yet empty geom column by parsing the well-known-binary objects from the geometry column into \n",
    "# Spatialite geometry objects\n",
    "engine.execute(\"UPDATE borehole SET geom=GeomFromText(geometry, 28352);\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we will add the hylogging data to the database. Note that this could be done \n",
    "# using the declarative base using a similar approach to that used above but \n",
    "# the number of columns and my unfamiliarity with the data makes this a too tedious a task\n",
    "\n",
    "#df_hylogs.to_sql(\"Hylogging_data_from_core\", engine, if_exists='replace', index = False)\n",
    "#df_hychips.to_sql(\"Hylogging_data_from_chips\", engine, if_exists='replace', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a metadata table and add it\n",
    "\n",
    "df_metadata = pd.DataFrame(data = {\"Depths\": ['metres below ground level'],\n",
    "                                  \"Conductivity\": [\"S/m\"],\n",
    "                                   \"GAMMA_CALIBRATED\": [\"counts per second\"],\n",
    "                                   \"GR\": [\"American Petroleum Index\"],\n",
    "                                   \"Magnetic_susceptibility\": ['Unitless_(SI)'],\n",
    "                                    \"U\": [\"ppm\"],\n",
    "                                    \"Th\": [\"ppm\"],\n",
    "                                    \"K\": [\"%\"],\n",
    "                                     \"water content\": [\"fraction\"],\n",
    "                                     \"Ksd\": [\"metres per day\"],\n",
    "                                    \"EC\": [\"S/m\"]})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_metadata.to_sql(\"Units\", engine, if_exists=\"replace\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Composite Log Creation Loop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Well ID</th>\n",
       "      <th>borehole_id</th>\n",
       "      <th>base_of_cenozoic_depth</th>\n",
       "      <th>base_of_ceno_elevation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KR8</td>\n",
       "      <td>635728</td>\n",
       "      <td>40.20</td>\n",
       "      <td>7.519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>KR21</td>\n",
       "      <td>635921</td>\n",
       "      <td>16.56</td>\n",
       "      <td>4.735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>KR22</td>\n",
       "      <td>635730</td>\n",
       "      <td>21.87</td>\n",
       "      <td>4.364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KR30</td>\n",
       "      <td>635733</td>\n",
       "      <td>34.19</td>\n",
       "      <td>17.506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>KR31a</td>\n",
       "      <td>635734</td>\n",
       "      <td>35.50</td>\n",
       "      <td>17.913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>KR33</td>\n",
       "      <td>635735</td>\n",
       "      <td>19.01</td>\n",
       "      <td>16.494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>KR38</td>\n",
       "      <td>635737</td>\n",
       "      <td>7.79</td>\n",
       "      <td>12.462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>KR40</td>\n",
       "      <td>635738</td>\n",
       "      <td>8.67</td>\n",
       "      <td>17.673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>KR45</td>\n",
       "      <td>635739</td>\n",
       "      <td>36.11</td>\n",
       "      <td>18.799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>KR46</td>\n",
       "      <td>635740</td>\n",
       "      <td>34.38</td>\n",
       "      <td>18.357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>KR48</td>\n",
       "      <td>635741</td>\n",
       "      <td>35.48</td>\n",
       "      <td>19.046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>KR49</td>\n",
       "      <td>635742</td>\n",
       "      <td>34.25</td>\n",
       "      <td>19.951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>KR50</td>\n",
       "      <td>635744</td>\n",
       "      <td>38.18</td>\n",
       "      <td>5.094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>KR54</td>\n",
       "      <td>635747</td>\n",
       "      <td>25.82</td>\n",
       "      <td>47.398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>KR55</td>\n",
       "      <td>635748</td>\n",
       "      <td>14.22</td>\n",
       "      <td>49.364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>KR58</td>\n",
       "      <td>635749</td>\n",
       "      <td>18.94</td>\n",
       "      <td>5.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>KR51B</td>\n",
       "      <td>635746</td>\n",
       "      <td>53.38</td>\n",
       "      <td>5.055</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Well ID  borehole_id  base_of_cenozoic_depth  base_of_ceno_elevation\n",
       "0      KR8       635728                   40.20                   7.519\n",
       "1     KR21       635921                   16.56                   4.735\n",
       "2     KR22       635730                   21.87                   4.364\n",
       "3     KR30       635733                   34.19                  17.506\n",
       "4    KR31a       635734                   35.50                  17.913\n",
       "5     KR33       635735                   19.01                  16.494\n",
       "6     KR38       635737                    7.79                  12.462\n",
       "7     KR40       635738                    8.67                  17.673\n",
       "8     KR45       635739                   36.11                  18.799\n",
       "9     KR46       635740                   34.38                  18.357\n",
       "10    KR48       635741                   35.48                  19.046\n",
       "11    KR49       635742                   34.25                  19.951\n",
       "12    KR50       635744                   38.18                   5.094\n",
       "13    KR54       635747                   25.82                  47.398\n",
       "14    KR55       635748                   14.22                  49.364\n",
       "15    KR58       635749                   18.94                   5.900\n",
       "16   KR51B       635746                   53.38                   5.055"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_interp = pd.read_csv(r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\stratigraphy\\base_of_cenozoic_picked.csv\")\n",
    "df_interp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to \\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\\East_Kimberley_borehole_data.sqlite. Temporary working copy created.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\skimage\\transform\\_warps.py:84: UserWarning: The default mode, 'constant', will be changed to 'reflect' in skimage 0.15.\n",
      "  warn(\"The default mode, 'constant', will be changed to 'reflect' in \"\n",
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\matplotlib\\scale.py:111: RuntimeWarning: invalid value encountered in less_equal\n",
      "  out[a <= 0] = -1000\n",
      "C:\\Users\\u77932\\AppData\\Local\\Continuum\\anaconda3\\envs\\hydrogeol_utils\\lib\\site-packages\\pandas\\core\\indexing.py:543: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connection to \\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\\East_Kimberley_borehole_data.sqlite is closed. Temporary working copy removed.\n"
     ]
    }
   ],
   "source": [
    "# Define the database path. Check this to ensure its up to date with the variables above.\n",
    "# Variable definition applied here just so this cell runs standalone\n",
    "DB_ROOT = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\"\n",
    "DB_PATH = os.path.join(DB_ROOT, r\"East_Kimberley_borehole_data.sqlite\")\n",
    "\n",
    "# connect to database\n",
    "con = makeCon(DB_PATH)\n",
    "\n",
    "# make query to extract all ENOs and borehole names from database\n",
    "bh_list_query = 'select borehole_id, Borehole_name, Alternative_name from borehole'\n",
    "# run query\n",
    "bh_list = pd.read_sql_query(bh_list_query,con)\n",
    "\n",
    "# Loop through each hole by ENO\n",
    "for i, (bhid, bhname, altname) in bh_list.iterrows():\n",
    "    plt.close('all')\n",
    "    # extract all the data for that borehole into a dict of dataframes\n",
    "    data = extract_all_boredata_by_simple_query(con, bhid)\n",
    "    \n",
    "    # draw the composite log for that hole. Pass only the file stem without extension, as the code creates .svg and .png\n",
    "    # note, when the output_path variable is supplied, the drawFunction only outputs to file\n",
    "    # remove this parameter to see the results inline\n",
    "    if altname is None:\n",
    "        output_path = r'\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\GAHoles_CompositeLogs\\{}_complog'.format(bhname)\n",
    "    else:\n",
    "        output_path = r'\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\GAHoles_CompositeLogs\\{}_{}_complog'.format(bhname, altname)\n",
    "    \n",
    "    fig, axs = drawCompLog(data, output_path = None)\n",
    "    \n",
    "    #plt.show()\n",
    "    if bhid in df_interp.borehole_id.values:\n",
    "        for ax in axs:\n",
    "            ax.axhline(y=df_interp[df_interp.borehole_id == bhid]['base_of_cenozoic_depth'].values[0],\n",
    "                       color='red')\n",
    "    plt.savefig(output_path)\n",
    "# Close the DB connection\n",
    "closeCon(con, DB_PATH)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing cell for a single hole's composite log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to \\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\\East_Kimberley_borehole_data.sqlite. Temporary working copy created.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\u19955\\AppData\\Local\\Continuum\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:543: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n"
     ]
    },
    {
     "data": {
      "image/png": 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GLZQvG8XqX37j9y3J1KqeQMe2txAebk1xXffbZlau3UBoaCgej4frWjalRkIc\nBw8fYffeA1StHMPM+UvZtWcfd9zcKniCNDh5wdy5U1FzrpX660SEcuXK8dHHH/lWw1T/SIOM3xL8\nIhKLdSF6KfCNiDQ7neF1xhiXiPTBCjIGiMiEIpLvxArm4gPtFJHSWEPO4ORFYDWs+VrHgSEBfhSI\nsZ8/F5E0YLwxZrBfeRRWnt/x/dMC3Ic1P2lGoMDKGPOjiOzC6iG7AmuRjEDnEwW0t18WOtTxXJWX\nzxqsHrGz6YU5nR7Ior78pwqkz9fPw/71PatzMMYsFZEErKGmrYAW9r/vAPqKyE3GmF/OQV29P1Uv\nJu9nL5CiAqJzobA2Kuo9Lqpd//6f/5UKYmvWb2TWgqVUia1EVOlS7N53kB6vDiK6TGlCHA4qVijH\nhGlzOHjoCM8+/gAbNm5l+rzFtLqqKTt37+Xz0WOJrVSBctFR5OQ4efu/w3jt+Se5tG4tRo39gbmL\nf6JuzSRCQhzMWfQjh48e54kuHVn76yZmLVhKpQrlKV4sgjKlSuF0Otl/8DCbk3dQtXIl6taszrS5\ni/hj127eee0FQkPy9qKNmzqbH2Yt4LJ6tTh2PIX0jEyiSpc6478smVnZ9P/gM9LS06ldI5HDR46x\nYOkKBr78LLWqJzDy+8kcO3aCuKqxlI2K4odZCzh67ATPPv4AG7dsZ+B/PqdShfJUianA1j92sXrd\nbwx9ry85Obm8PXg45cpGERkeTrHISIzHBFeQ5vXNt99qT5o6b/yv2bXT9uJijNkvIh2xhtw1Be6n\n8OFl+Y3FWkGvEfBoEenWYgUthf333tR+TjYFl+iP5uTwrEAa2c/r/LattZ8Dlmev/heNtViE/xwk\n75yoonpNvL1Zha1wCNAJq1doJ9aKlIU5V+X5m4I17+pmEalkjDnVap3+vD1dSUWkSbSf957Bcf+q\nBE6umph/O8A+v21nfQ72MN6x9sP7A8aHWD3Fn2AFbn/Vbvt5nDHmk3NwvLOxF+sm9kmc7DXzF6h9\nvG1c1A8fRe1T6n9Oalo6pUqW4D/9/w+AtPQMur88gGtbXMHdt98EwOKfVvPtpOkAlCpRnPAwqwcp\nPcOarvpW7x6UKG71Ur310VAWL/+ZS+vWYs2G3+nX62nq1rT+q/tp9S8M+2YCT3TpiMfjoUZCHP16\nPU1Y2MmwpeWVjWh5ZSPf66qxlRgyagzGGCIj8yx4y4o1G7jrthu5r30b/oqFy1ZSLDKCj998hRCH\nNWPsmd5vsnHrdmpVT8CV6+KBe9py243Wn/l5S5Yzdc4iAJauXEO92tV548XuAKSkpvHCG+/y2+Zt\nlCldChHhxacepnrCySnSQROLOknkAAAgAElEQVSkSWE3PlbqHNPP2MXNGLNZRD7FWiigr4iMsecK\nnSqfEZGXsXriXgNmFpL0B6xl2NuKSKkAgZh3KMAkv2PvpIjfA+TkzbkL3Mwaa55dLtBCRBIDLPrg\nLW96vjlS3gvRgPeJshdy8M5XKmo4nXchiy9P0St5rsrzMcYsFJHlWItTDBGRu4saKioijYGN9qIV\nS7F+h2kmIrXyL6IhInWxFnHxYC3a8Xe5H+szFGg7WCstei22n+8Qkej8PZT2QjexWEMs1xRVqP0D\nRm+sIK3BadbV+3kq7FphJtYPGvdgBX4XwmKsIK0LgXtnvXMgF/lt8342WohIvDEmTy+f3a6n+0OC\nUv8TnLm5lIuO8r0uWaI4lStVpErMydHoUWVKU7xYsQJ5XS4XEeHhvgDNyl8iz/XYgmUr+XXTVhwO\nB2vW/07lStZxs3NyqF0zMU+ABtbcsRFjJpOalk7JEsU4cOgoIQ6Hdcx8f6rq16lhLwZicLk9OJ25\nXNu8CTUSC1vfKTCX2016Ribjp87B7bbWjNp/8DDFi1mj20uUKE5c1Vhf+sjICN8+l9vN8ROpTJg2\nB7fHw74Dh0hNy6Bi+bKkpKYTU7E8SfFV85QXVAuH6MWzUuocGYg1P6s68MDpZjLGzMHqLYrBupgN\nlOZXYDrWkMah4nczYRFph3WxmIm1PPtfZi8YMRTr/+svxe/mwPa93V7CXoY9X1bv0v3NReRlEXH4\n5SuDtaBCJNZCGAEv8EXkMqzePQ+FL8xwzsorRGesRWHaA5PtYXz561lWRPpjLasfAWBfeE/AarfP\n7Tp400dhrcToAMbaKyX+XTqISAf/DSLyONawxHT8hpQaY7z3XysFfOJ/PzQRqcLJz9hg78qPIhIv\nIo/aw27zu8N+Pt2hh97ep7qF7J+M9V5eKyKfBbrnnIgkiUi30yzvbHyMtUrjfSLS3n+Hfd+5jlg/\ncnzs3W7/0DEdK/j8RPxuai4ilYD3zmN9lboouN0enLm5uP0WBsl1uXzBy+nwXvWLCH/s2s3vW5JZ\ntXYDxYtF8sSDHQHwuD3k5DgL5P3v8G/Ze+AgN193Fbdefw0tmjbEYfdueYzJE6d1uus2Lq1bk3W/\nbWb7jj/5afUvvD9kJBmZWWd0zmFhoWRkZrFp63Z+35LM2g0buanVVdxwTXNycpy43W5crpPn73F7\nfKO3HCIcOXqc3zZv45dfN7Fn30Eeuq89FcuXIyMzC5fbjSdfcBk0PWlKKXWuGGMOi8h7wBtAHxH5\n6nR602wvY93ktvCZw1bvwY9Y92FqLiIrsBYjuAoroHnIGLOviPxnqhfWMMpWwHYRWYy1cmJrrHlB\nL+SfY2SM+VVEXsPq9XsTeFRE1mMtz94Uq6cgFeicbxl5f95etDmnCmTOUXmBjvuHiLTACgLvAG4T\nkXVYC2Z4sHogm9jtsAPI8cv+JFbvXSvgDxFZZG+/DmuI6Hqse5v9nT4GxtufmR12/Rpinctjxpj9\n+dJ3AhZizfm7VkSWYX02r8O6gfl8rFVDvaKxbhj+id1OO7CC0XpY9xDMxQrsT8dsrB8c7hKRJVjD\nCd3AFGPMFGOMx17RcwbwBNDJfs/3AOWxhsDWwrqp/Jn2tDWy26gw040x/Y0x60XkWaz7Gk4UkZV2\nPWtgfe48QHf7xxV/TwKXAbdhfTaWYAX412HdJ20FVq9wwatDpdQ54e2ccbvdPP1IZxKqFVwU1xQy\ndTQ7J4fbb2zFDdc0B6zFQeY5T35dvUMsAcqUKsnzT3b1vU5JTeOZ3m+y78Ahaiad/shmpzOXxLgq\n9H2x4J8NZ25uwDwejxXEuj0eGl5alxe7PVwgjdsT+E+iBmlKqYvVB8BTWHNVHqToRS98jDGr7IVD\nOhSR5oA9tK43Vg9Pe6wAZArwpjFm1V+se/7yMkTkGqz7N3XCClaysXr93jfGzC4k3wAR+RErEGmG\ntXiEG2t+2dd23j8D5RWRcE4OwfsyUJpzWd4pjrvF7tW7F7gLa35ePawfYg9g9ehMwFpwJdcv3xER\naY41r60jcKu9axtWb8lH/vfI+pt8hBUA9MS6V5cHmAf0N8YUGHZpjEkWkYZYgVU7+5GLFUiMBob6\nnzNWgNITKzCtbz88WL1iQ7HOeePpVNT+nN+ONfy3IdASq833YH3WMcbsEZGmWAF9R6xFe64Ejtpl\nvoff0N8zUMo+TmF8t1UwxnxqB4fPY/1Q0hir93Ui8J4xZnmAc/PW+w2s96GdXd8h9rYNdtIjZ1F3\npS56xhhyXS5cfvdBc7vduOyeNGdu3n35eTweUtOsnqy4KpUZ8MEQ2txwDbkuNydSUqmZFE/rllfi\ndnsC9s5FRoQzb/FPOJ1OftuczPadfxISEoLTmcsVDS5hxHeTeP3dwTxwT1uKRUayYOkKQkNDCQ8L\nZc++g4SEhFiLh5yBKxtdxpjJM3ln8HBqJsXjdOay/9Bh2lx/DbWqJ5Cb6/KdP1jDPJ1O67/nejWT\nGDLqe74aN4Xw8HBcLhc5TicP/utOikVG4sxx4nF7fHPdAOQ0Fj77u/wtFbmQ894udNlQcEipwSDn\nYOkM37n9xZU48reRObkD+FvmLuqYW6XUOec37zAx0L25VPCwh9QmY91APvoMb5mhVDA459fUM+Yt\nIS09g3/daf3W5fZ4GPvDLBo3qE8tuzdq5+69/LjqF+7vcDubt/3Bz+t/p/Pdd7B63W+s3bCRJ7p0\n9B1v3pLlOHNzaXP9NRw+cowvx0ziwKEjhIWGEOIIoX2bG2ja6FLmLVlOSEgI113VNE999h88zBdf\nj+dESirNmjSg8WX1+eW3Tdx0bQtKlyrJkuU/883Eadxx03VcWrcmY3+YRVp6BlnZ2QDcdsO1tMp3\nTIDV635jxrzFvP5C4EEWP6/7je9/mOV7HVWmFF3vbU+VmIp8PX4qVzdrTHxVq0dwy/Yd/PLrZu61\n22zSjHks/HEVkRHhANSvXYMH/3Un+w8eZu7in+h89x2+IZtwEQVp/hfuxhj279/Prh07ycnJISo6\nmrr16hIRHsHhI4cpX778eQ+WvO3qcrlYuWIlTa5oQkSENZ3gQgRqJl+Qs2/fPipXrnzO6uP/OTrb\n42VmZnLk8GEASpYqRXR0NB6Ph59XryYuLo7YypX/jkBXgzSl1DmnQVpwEesPSeP8C/WISDWsG7a3\nxJrr9/SFqJ9Sf1HQXNz/0yxbuZaxU2bx8cBXLnRVgmvhkL/Ce+F+5PBhnu7WnVtuupmffvoJEWHN\nzz/Tvt2dPPLww8ycWdiCbeenPgP69+PBBzrx+quv5dn+d/IGNt4AzRjD3Xd1IDfHeU7rs3HjaY2g\nKbSOuU4n3Z7qRqtrr+XTTz5BRFixfAWd/tWRRx8tOIZXKaWUOkshwGoR2SUis0VkjD1UdytWgPYb\n0OeC1lAp9berViWGW65reaGrAVxEQZoxhuPHjnFX+/bMnD6N4SO+5LkXnueaVtfy8KOP8MPUKRw9\nduxvr1fz5i2Iia3Klc2aXbChjv7BGcD+ffs4eGA//fr1O2dlHDl8hCcee/ys8nrrVSYqiiuuuAIx\n1phJYwwxsTFUS0igUcMmgK4AqpRS6pxwY60Cux9rvt1dWAuJbMQKzpobY4q6559S6iIUX7UybW64\n5kJXA7iIFg4REXq/0pu9e3Zz6WWX0aRJE19wAhAaGsqnn37KkiWL88xrSk5OxpmTQ63atQkNDfVt\nz8zIZPv2ZIoVK0ZS9ep5xogmb9uG05lLjZo18Hg8REZEYgRST5xg585dlC5dioTERFwuF1c2a8b0\nGdOJiIjwHTsnJ4ctm7dQtlxZqlSpgsGQcsL6WxAREUFISAibN20iMTGJ0mVOrqLsys1ly+bNiMNB\n3Xr18pzHrp07OXEihUsvuxRxOMDebowBO7Dxvu7erTuCYcLECfQfOMAX+OTk5JCZaa2GU7JkSZxO\nJ7lOJwaIirLujeFxe9i0aSMlSpakYoWKFC9RnGNHj9KhfXtynU5STpwgPDwCj/Hgsle6KRMVRUZG\nBrt376ZuXWsl59TUVHbu2EloWCh16tTJ074GA8bg8XgoW7Yskyf/QEio9VH1vp+7/9zN0aNHiYmp\nRGzlgqsBKaVUMDHGJFzoOqiT7Hv+9UF7y5RSQeqi6UnLzMxkwfx5GAzXXncdkHcelohQuUpl2t15\nJ8YYXLkuHn/0MUaNGMlXo7/igfs7k2UHKGt+XkPzZs1YumQp/d7oR6d77yMtLQ1jDG+/NYiePXqy\nctVKrrmqJTt37sQIzJs7l+taXcemjRu56cab6N+vH+np6dx77700atiQtwe9DcCWLVu4smlT9uze\nTft2d/Lt19/gcXu471/30vjyRnR/qhsP3N+Zu9rfxRVNmpCdnY0xhj2799CkcRO2bt1Gu7btuOvO\n9ng8HkSE1/q8Sq+XerF+3TpaNGuOy28JUpGTy4IYY0hLS6N27dp4cJCbncW4seN8+w4fPsyVVzSl\n8eWNWL58OVu3bKXR5Y1o1LABGRkZuN1u7u/UiS++GMrEiRO5umVLnE4nL734Env27CElJYVnnnmG\nsWO/Z/369TS8vCGNGjZi86ZNNGt6JXfc2oajR4/y348+5t9P/Ju1a9fQ7o623HN3B9xu98l5bQIO\ngdzcXD788EMaNbycLg9Yt7o6evQoHe++h2nTpvLN11/T8qqWfP3VV3neb6WUUkoppf7JLpogLTk5\nGZfd61OtajVfYJZnpUBjiIyMRER46603mTt3Lk92e4rer73K6pUrmDZ1GsYYnu72JJkZGTz2xOP0\nG9Cf1StXMLD/ABBh3NixOBzQoUMHPv3sM+sme9nZPNejJ/fccw//uu9eypYty4gvRxAWFsa111yL\n2AtDiQid7r2P2IoVaXP7bbRt25Y+ffqQlZXFda2vQwT2H9jPmLHfExMTg9tp9ZwBtGvbllynk3Z3\ntadKlSqsW/cLbrebubPn8PXXoxj11WgeeLALhw4dokePnoW208ABA3nzrTdp0KABGBg4YIBvX5Uq\nVahatSqCAY/hkksvAcCBdff2w4cOsWrVKopHRNKzZ0969uxJeHg4/fr3ByAqOppRo0fT9aGHaNq0\nqRUcGsNH//mIvn37ctXVV3P8+HE++vBDcp1OHuzalcTEBNatWcuvGzZYPX0CiGCwehXb3GqvmG2s\nGwKOHjWKtWtWk5SUxONPPI7xGEYMH3ZuPkRKKaWUUkoFgYtmuCNYS9k4kDz3U8jKymLZsmXkZOf4\nUtWoWZPFCxbiwMPyn34iIiIScTiYPmMG8YkJHDxwkAoVKxEWFkZMTAwIjP1+LK+/0ZfIYsX49ddf\nub7VdQwdNoxatWvx3bffkZmeQZUqVRARhnw2hBMnUihZsiRhoaEYO1A8cOAAKcePk5gUz7Sp0zhx\n4gQOhMOHDhERHoHgoeHlDRERoqKiOLhvL0ePHCUnJ4eU40epFp+IQ4RJkyYxa/ZsQkJC+L//+z8c\nCHPnzAWspQnnzDq5NKj/oiHOnBz+/PNPHCEhDP5kMNe0bElaWgq///ob9S6pD0BYaCggOBwOK8D1\nxbhCWHg4GBg7biwbN29hyGef+YJg/6GlvhUY7V68hx56iKbNrqTDPXeTmZVFuzvvpHqNGmzetIkT\n9jDPzIxMKx+CGN+K+4gIDoPvNgGtW1/Pli1bqVq1GitWrEDEurlg/tU9de6aUkoppZT6p7poetJq\n165NZLFiAOzdt9e3UEZkZCTNmzfnlV696NG9O2vXrKVO7TqkpKVhRIiPj+OSS+ozd/583nzzTfbs\n3mP14kRGYoyxhuEhGAzZ2dm898H7lC5VmmNHj9ChfXt+2/ArycnJIIbff/8dYwyNGjem9fWtTw6/\nM1aw8cf2PzBY87EuuaQ+Tz/zDPMXLfQtLQ9YPUn57Nu3D7eB3Xv2YDyG6HJlua/TfTgcDlJSUjBA\n/Xr1qH9JfeYvXMjc+fOtY/nNSzPG8NVXXxMfF8dbb77JqFGjcISEAPB09+4FyjTGjpSMdx1XQ/ly\n5Xj19ddAhF9/3cCtt9xCWloaCIgBh7f30hvZGcAY6tSr69tevHhxXu7Tmy1btzBhwkTKlS1rta+v\nrU4OefR/abCOfXnDy+nU6T569+6NiMPOdzI40yGPSimllFLqn+6iCdLCw8O5o92deIzVq+Q/H61E\niRKUKFUKI4aExASMQOnSpTEIWVk5xCUkEJ+QQEhoCPXsgMLlsha9yMnJQYwhIiKCEiVKUKVKFeYu\nWECDhg1xiGHIkCHUqlkTjIcpU6aQk5NjxyZ+9w3DCh4SkxIRYHtyMjGxscQnxJOQmODrtTJ2UOTt\nwfJgDf+rXLkyIg48bhcZmRl5gpEyZcqAgeXLl5OQkEBCYgIRkSfvx+ZN53a7+eabrxk0aBAvv/IK\nvXv3YdSo0Rgj7Nn9J8eOHbMCKYcDDx6/+hvfWWRmZdGxY0cmTvqBChXKk5aWwrixYwHwiDmZzy/Q\nFBFC7GDQYDhx/Dg33nA9WzZvoc+rffKVYQWp3iDP2w7eMMwYw9QpU3moa1c6dOhAs+bNfPn9b8it\nvWhKKaWUUuqf7KIJ0kSEfv370aJFC7Zu3sTEiRMB+wLfe9Fu7F4eY7juuutwGEOvF19gzeqfWbRw\nEatWraJOnTrUqFWbgwcP4XQ62bZ1Gx6EHj17EBYeTq8XX6J48eJMmDCR0qVLU6tWTTre+y9KlS6N\nMyebfq/3ZcO6dQx6axCpqalkZWeBCE6nk5iYGMqWKwceGPBGP7YnJ/Pee+/hdDrJyMgAHOTai344\nc5wIkJWZSUREBLGxsTgwdOxwN7+sXcv3341h//79vPXWWyDQp08flv/0E7+sXcunn3yaZxgiwKQJ\nE+n1Ui+M2D1OGK64sikiBrfbRfenngSges0aOATWrV/Hzz+vsY5hrJtyZ2Zm8lyPHjS4vAFjx48H\noFat2oSFhQEGZ3Y2KSkp/LhsGR63B4PBY6/S6A36tidvJ/XEcY4dO8p3337H4cOHQaw5hbm5uRiX\nGzC4XdaQVY/bWhwl1+UCYOz33yPGw4rlPzFu7DhfG+3atSvPcEellFJKKaX+qUL69u17oevg1fev\nHiAkJIT2d7WnQsWKfD36K+bOmcPG337nh8mTyc3N5dY2bbirQwdKlylNy6tbsm/ffjZv3sy0qVMp\nXaY0D3V9CHEIN950I5s2bmLNz2uY8sMPtGnThmeefZaQkBBmzZzFgvkLWL5iOSGhYbzW93WKFy9O\no8aN+XXDryxfvpz169bRrXs3SpUqxZgx31OiZElycnJo1aoVbdq04Zd161m2dCmLFi3m0cceo1q1\nanz11WiKlyhBTq6Ta6++hrnz5lKuXDlSUlO54YYbuKfjPaxZ8wtbNm1i6ZKltGh5FVc0bUr1GtU5\nfuIEO3fuZNLESaSkpPLuu+9ay9jbFi5cyOeff86x48coX6EClStXxuPxsHDhQnbs2EnFSpVwuVxE\nRkTS6f77mTVjJitWrKRkyZLkOHOoWLES2Tk5NLisAePHjWPFihUsWbKEyxpcziOPPkKJ4sVx5uSy\na+cu1m/YwBNPPM7KVStJ3raNCpUqket00qSJdZ+zYsWKsXLlSopFFqdxo0a0uOoqtmzdSqlSpWhw\neQPGTxhPyRKlkBAHl19+OVOnTSUrK5tixYpRo2YNatSozq+//kZUdDSPPvooO3buxIOhXr16JCYm\nFghOz8Ibf/FjqJRSSil1IfW90BVQf50EUa/DOa3I6Swk4T9ny9rtN5cq0DW+/3bvXCi/dKezYEWR\naYw1JFDs4+atX8HnQsvg5PDA0wlW/NOfPKXA+byLe1j57Pp4Uwdot/zvA/gNw/Qb2nha7eI9d2/7\nFFHuX6BjJZVSSin1TxY0F/fq7F20QZpSZ0mDNKWUUkr9k+k19UXgopmTppRSSimllFIXg4vqPmlK\nKaWUUkr9j9NRQRcB7UlTSimllFJKqSASTD1pGvUrpZRSSiml/udpT5pSSimllFJKBREN0pRSSiml\nlFIqiGiQppRSSimllFJBRIM0pZRSSimllAoiGqQppZRSSimlVBDRIE0ppZRSSimlgogGaUoppZRS\nSikVRDRIU0oppZRSSqkgokGaUkoppZRSSgURDdKUUkoppZRSKohokKaUUkoppZRSQUSDNKWUUkop\npZQKIhqkKaWUUkoppVQQ0SBNKaWUUkoppYKIBmlKKaWUUkopFUQ0SFNKKaWUUkqpIKJBmlJKKaWU\nUkoFEQ3SlFJKKaWUUiqIaJCmlFJKKaWUUkFEgzSllFJKKaWUCiIapCmllFJKKaVUENEgTSmllFJK\nKaWCiAZpSimllFJKKRVENEhTSimllFJKqSCiQZpSSimllFJKBREN0pRSSimllFIqiGiQppRSSiml\nlFJBRIM0pZRSSimllAoiGqQppZRSSimlVBDRIE0ppZRSSimlgogGaUoppZRSSikVRDRIU0oppZRS\nSqkgokGaUkoppZRSSgURDdKUUkoppZRSKohokKaUUkoppZRSQUSDNKWUUkoppZQKIhqkKaWUUkop\npVQQ0SBNKaWUUkoppYKIBmlKKaWUUkopFUQ0SFNKKaWUUkqpIKJBmlJKKaWUUkoFEQ3SlFJKKaWU\nUiqIaJCmlFJKKaWUUkFEgzSllFJKKaWUCiIapCmllFJKKaVUENEgTSmllFJKKaWCiAZpSimllFJK\nKRVENEhTSimllFJKqSCiQZpSSimllFJKBREN0pRSSimllFIqiGiQppRSSimllFJBRIM0pZRSSiml\nlAoiGqQppZRSSimlVBDRIE0ppZRSSimlgogGaUoppZRSSikVRDRIU0oppZRSSqkgokGaUkoppZRS\nSgURDdKUUkoppZRSKohokKaUUkoppZRSQUSDNKWUUkoppZQKIhqkKaWUUkoppVQQ0SBNKaWUUkop\npYKIBmlKKaWUUkopFUQ0SFNKKaWUUkqpIKJBmlJKKaWUUkoFEQ3SlFJKKaWUUiqIaJCmlFJKKaWU\nUkFEgzSllFJKKaWUCiIapCmllFJKKaVUENEgTSmllFJKKaWCiAZpSimllFJKKRVENEhTSimllFJK\nqSCiQZpSSimllFJKBZHQC12BYFGsWLED2dnZlS50PZS60CIjIz3Z2dn6A45S6PdBKS/9LihliYyM\nPJiVlRVzvssRY8z5LuMfQUSMtoVSICLod0Epi34flLLod0Epi/1dkPNdjv4iov7RRITk5OQzzrdz\n505EBJfLdR5qpVRwSEhIoFixYpQsWZKYmBi6du1Keno6AF27dkVEWLVqlS99cnIyIif/7uTk5PDw\nww9TunRpYmJi+OCDDwKW88YbbyAizJs377Tzjh07lrp161KqVCnq1avH5MmTffv+/e9/U7JkSd8j\nIiKCUqVK+fbv3LmTNm3aEB0dTUxMDN27d9fvchDp2rUrffr0udDVKNTSpUupXbv2ha6GUv+TEhIS\n8vytGDNmDNHR0SxevBgR8f2/n5CQwKBBg/Lk7dy5M7GxsZQuXZpatWoxbNgw376NGzfSpEkToqOj\niY6O5oYbbmDjxo1/23mdDxqkqXPO/8IwOjqa2267jd27d1/oain1P2nq1Kmkp6ezbt06fvnlF956\n6y3fvrJlyxZ5Md23b1+2bdvGrl27WLhwIe+88w6zZs3Kk2b79u2MHz+e2NjY0867d+9eOnfuzAcf\nfEBqairvvvsunTp14tChQwB89tlnpKen+x733Xcf99xzj+/YTz31FBUrVmT//v2sW7eOxYsX8+mn\nn/7ltlJnrlWrVkRHR5OTkxNw/6JFi6haterfXKu88v+Yd/XVV7Nly5YLWCOlFMCoUaPo1q0b06dP\nJz4+HoATJ06Qnp7O+PHj6d+/P3PnzvWlf/nll9m5cyepqalMmTKFPn36sGbNGgAqV67M+PHjOXbs\nGEeOHKFt27bce++9F+S8zhUN0tR54b0w3L9/P5UqVeLpp58+42PoL+NKnTsxMTHcfPPNrFu3zrft\nwQcfZMOGDSxevDhgntGjR/Pqq68SHR1N3bp1eeyxxxg5cmSeNN27d+ftt98mPDz8tPPu2bOHqKgo\nbr31VkSE2267jRIlSrB9+/YCdcjIyGDChAk8+OCDvm07duygY8eOREZGEhMTwy233MLvv/9+li2j\nztbOnTtZunQpIsKUKVPOSxn6d0Cpi9PQoUN5/vnnmT17Ni1atCiwv0mTJtSvXz/P36z69esTEREB\nWD++iIjv70ZUVBQJCQm+YbkhISFnNdIqmGiQps6ryMhI7r77bl+Xc0pKCl26dKFChQrEx8czYMAA\nPB4PACNHjuSqq66iZ8+elC1blr59+wLw5ZdfUrduXaKjo7n55pvZtWtXnjLmzZtHzZo1iY6Oplu3\nbr4x8x6PhwEDBhAfH0/FihXp0qULKSkpAeuZkpLCI488QmxsLFWqVKFPnz643e4iz23kyJG0bNmS\nF154gejoaBITE5k5c6Zv/4gRI3zDuZKSkvj88899+7y/Lr/zzjtUrFiR2NhYJk+ezIwZM6hVqxZl\ny5blzTff9KX3eDwMGjSI6tWrU65cOTp27MixY8dO811QygqMZs6cSY0aNXzbihcvziuvvELv3r0L\npD9+/Dj79u2jQYMGvm0NGjTIEwyNGzeO8PBw2rRpc0Z5mzRpQt26dZkyZQput5vJkycTERHBZZdd\nVqAeEyZMoEKFClxzzTW+bc8++yxjxowhMzOTvXv3MnPmTG655ZazaBX1V4wePZpmzZrRtWtXRo0a\nVWB/RkYGt956K/v27fMNYdq3b1+R/595h6IPHz6cuLg4Wrdu7ds2atQo4uLiKF++PAMHDvSVs2rV\nKpo3b05UVBSxsbF0794dp9MJ4PvcNGjQgJIlS/L999/n6d0bNGgQd999d556P/vsszzzzDOA/m1Q\n6nwYMmQIr776KvPnz6dJkyYB06xYsYLffvstz98ssEZSFC9enDp16hAbG1vg709UVBSRkZE8/fTT\nvPLKK+ftHP4Wxhh9WJ45oq0AACAASURBVBf1Rp0b8fHxZu7cucYYYzIyMkyXLl3MAw88YIwx5oEH\nHjBt27Y1qampZseOHaZmzZpm2LBhxhhjRowYYUJCQszHH39scnNzTWZmppk0aZKpXr262bhxo8nN\nzTX9+/c3zZs395UFmNtuu80cP37c7Nq1y5QvX97MnDnTGGPM8OHDTfXq1c327dtNWlqaad++venc\nubMxxpgdO3YYwOTm5hpjjGnXrp15/PHHTXp6ujl48P/ZO++wqI7uj3+XXdhdYGHp3QVRRLELMVaI\nMdgQUZEmEbEHyc+WoqIUxRq7xAZvxAZqjLFjS0SxEZOIvmhUUCmyCtJBWGCX+f1BuC+XriK2+TzP\nPs/eO+3M7M6cO3dmzskkdnZ2ZNu2bY3Wc+fOnYTH45EdO3YQuVxOtmzZQoyMjEhlZSUhhJATJ06Q\n5ORkUllZSWJjY4lQKCR//fUXIYSQCxcuEC6XS0JCQkh5eTnZsWMH0dXVJZ6enqSwsJAkJiYSPp9P\nHj58SAghZP369aR3794kPT2dyGQyMm3aNOLh4dEiv1dtaF/4cJBIJERNTY2oq6sTAGTQoEEkLy+P\nEEKIj48PCQgIIDKZjJiZmZFTp06RpKQk5vdPS0sjAEhpaSmT39mzZ4lEIiGEEFJUVETatWtHHj16\nxJRV3e+bSksIIREREURNTY1wuVwiFArJiRMn6q3DoEGDSFBQEOve3bt3Sc+ePQmXyyUAiI+PD9Pv\nWhraHxrG0tKS/Pjjj+TPP/8kPB6PPHv2jBDyv/8WIVVjnYmJCStdY+NZ9dj85ZdfkuLiYlJSUsLc\nmzJlCikpKSEJCQlERUWF3L17lxBCyJ9//kmuXbtGKioqyOPHj4m1tTVZv349Ux4AkpSUxFzXlCkl\nJYUIhUJSUFBACCFELpcTQ0NDcu3aNUII1Q01oX2B0hJIJBIiEomIs7MzUSgUzP3qfq6pqUkEAgEB\nQObNm1fv2C6Xy0lcXBxZunQpKS8vrxNeXFxMfvzxxwb1yuvyb19483OT1ijkffjQwaflqH4w1NTU\nJFwulxgZGZHbt28TuVxOVFRUyJ07d5i427ZtI/b29oSQKsVmZmbGymvo0KHMJI4QQhQKBREKhSQl\nJYUQUtVR4uLimPBx48aRFStWEEKqHu5+/PFHJuzevXuEx+Mxirx6kvbs2TOioqJCSkpKmLhRUVHE\nwcGh0Xru3LmTWFpaMtcvXrwgAMjTp0/rjT9q1CiyYcMGQkiVIhYIBEQulxNCCCksLCQAyPXr15n4\nPXv2JL/++ishhBBra2ty/vx5JkwqlTJ1aWloX/hwqDlxio2NJcbGxszDas0H6R07dpBevXqRBw8e\nML9/bm4uAUAyMzOZ/A4dOkQ6d+5MCCFk7ty5JCQkpN6ymkp77tw5oq2tTW7cuEEUCgX5448/iKGh\nIbl58yZL/rS0NMLlcpkHUkKqxgAzMzMSGhpKZDIZyc7OJs7OzuTbb79tmUarBe0P9RMXF0d4PB55\n/vw5IYSQDh06kHXr1hFCmp6kNTaeVY/NNX/z6nvp6enMPTs7OxIdHV2vbOvXrycuLi7MdWOTNEII\n6devH9m1axchpOplQtu2bQkhhOqGWtC+QGkJJBIJ2bdvH7G2tia+vr7MJKzmc5lcLidr1qwhvXr1\nImVlZQ3mNX36dLJx48Z6wxQKBdHW1mbpoZaitSZpdLsj5Y1w5MgR5Ofno6ysDGFhYbC3t8eTJ09Q\nXl7OHA4FAIlEgoyMDObazMyMlU9qaipmzZoFsVgMsVgMbW1tEEJYaQwN/+eqQlVVlbFeJ5VK65Ql\nl8uRmZlZp4yKigoYGRkx5UyfPp0xYtAYtcsGwJQfExODTz/9FNra2hCLxTh16hSys7OZ+Do6OuBy\nuQAAoVAIADAw+J+rPqFQyOSVmpqK0aNHM/J17NgRXC63Tl0olIawt7fHxIkT8c0339QJ8/X1RUFB\nAX799VfmnpaWFoyMjHDr1i3m3q1bt2BjYwMA+O2337Bp0yYYGhrC0NAQ6enpcHNzw6pVq5pMm5CQ\ngIEDB8LW1hZKSkqws7ND7969WRa/gKrtdH379kXbtm2Ze7m5uUhPT4e/vz/4fD50dHTg6+uLU6dO\ntUxDUZrFrl274OjoCF1dXQCAl5dXvVse66M541ltXQA0PNY/ePAATk5OMDQ0hIaGBhYuXMgaa5vC\ny8sL0dHRAICoqCh4eXkxclLdQKG0PPr6+vjtt98QFxcHPz+/OuFcLhfz5s2DQCBo1CiUXC6v9ywz\nULUVuHpL/PsKnaRR3ihcLhdjxowBl8vF9evXoayszDpTlpaWBhMTE+a6pvlvoEpRb9++Hfn5+cyn\ntLS03kOmtTE2Nq5TFo/HYym76jL4fD6ys7OZMgoLC1/LEEFZWRnGjh2Lb775BpmZmcjPz8fw4cOr\nV21fGjMzM8TExLDaQSaTsdqOQmmK2bNn49y5c6yD2ADA4/EQHByMVatWse5PmDABoaGhyMvLw717\n9xAeHo6JEycCqJqkJSYmIiEhAQkJCTA2Nsb27dsxc+bMJtPa2dkhLi6OkePmzZuIi4urcyZt9+7d\nTJpqdHV1YWFhga1bt0IulyM/Px+7du1inX+jvFlKS0tx8OBBXLx4kZmkr1+/Hrdu3WJNzIG6YzrQ\nvPGsvnQN8dVXX8Ha2hpJSUkoLCzE8uXLX2qsHTduHGJjY/HkyRP8+uuvzCSN6gYK5c1hbGyM33//\nHadPn8acOXPqjTN//nysXr0aMpkMWVlZ2L9/P4qLi6FQKHDmzBlER0dj0KBBAIBz587h5s2bUCgU\nKCwsxNy5cxnDVe8rdJJGeaMQQnD06FHk5eWhc+fOcHNzQ0BAAIqKipCamop169bB29u7wfQzZszA\nihUrGKVYUFCAn3/+uVlle3p6Yv369Xj8+DGKi4uxcOFCuLu7g8fjseIZGRnB0dER8+bNQ2FhISor\nK/Hw4cMGLd41h/LycpSVlUFPTw88Hg8xMTE4e/bsK+c3Y8YMBAQEMJPO58+f4+jRo6+cH+XjRE9P\nDxMmTMDSpUvrhHl6etYxox8SEgJLS0tIJBLY29vj22+/ZQx06OjoMA/ohoaG4HK50NLSgrq6epNp\n7e3tERwcDFdXV4hEIowdOxYLFy6Eo6MjU/a1a9fw5MkTlun9ag4fPozTp09DT08P7dq1A4/Hw/r1\n61usnSiNc+TIEXC5XNy9e5eZpP/zzz8YMGAAdu/ezYprYGCAnJwcltGmlh7PioqKoKGhAXV1ddy7\ndw9bt26tI8OjR48aTK+npwcHBwf4+vrCwsKCeaijuoFCebOYmZnh999/x6FDh7BgwYI64SNGjICW\nlhbCw8PB4XCwdetWmJqaQktLC9988w02bNiAUaNGAagy3e/p6QlNTU1YWloiOTkZp0+fhkAgaO1q\ntRi8pqNQKC/PyJEjweVyweFwIJFIsGvXLtjY2GDz5s34+uuv0bZtWwgEAkydOhWTJk1qMJ/Ro0ej\nuLgYHh4eSE1NhaamJr744ot6H9xqM2nSJEilUgwcOBAymQxDhgzB5s2b6427e/duzJ8/H506dUJR\nURHatm2L77///pXrLxKJsGnTJri5uaGsrAwjR46Es7PzK+c3a9YsEELg6OgIqVQKfX19uLu7M4MT\nhVIfKSkpde7VfoCtRklJCYmJiax7fD4fP/30E3766aeXLquptP7+/vD3928wvz59+uDFixf1hnXv\n3h2xsbFNykR5M+zatQu+vr5o06YN676/vz/+7//+D4MHD2buWVtbw9PTE23btoVCocDdu3dbfDxb\ns2YNpk2bhtWrV6NHjx5wd3fH77//zoQHBwfDx8cHpaWl2LFjB/T19evk4eXlhQkTJmD16tWs+1Q3\nUCgtS21dYWFhwfjSrd52XA2Hw2GtXDf2gmTcuHHNejZ8n+C86hL7h4ZQKFTIZDK6skj56BEIBJDJ\nZG9bDArlnYD2BwqlCtoXKJQqBAJBZWlpKfdNl0Mnaf/C4XAIbQtKazJs2DB4eHiwnPS+C1Q7gqRQ\nKLQ/UFoeDoeDpKSkOv6fAGDfvn3YtWvXa22BfFPQvkChVPFvX2j+wdlXhK4cUSj1YG5uDqFQyDhg\nVVdXb3RrVlMEBwfXOXsXExPzzk3QKO8PDg4OEAgEzP+zQ4cOTFhUVBQkEgnU1NTg4uLCcm7bWLoL\nFy6gS5cuEIvF0NHRwejRo1mWscrKyjBp0iRoaGjA0NAQ69atY8kUERGBdu3aQV1dHUOHDoVUKm2y\nHklJSRAIBA2eTfX19QWHw0FycjJzLyUlBcOHD4eWlhYMDQ3h7+8PuVzedKNRKE1gbm4OAwMD1lbb\niIgIODg4vFJ+Dg4OiIiIaHb88ePHv5MTNMq7Q0Pj34MHDzBq1Cjo6elBW1sbQ4YMwf3795l0ZWVl\nmDNnDoyNjaGlpQU/Pz9UVFQw4d7e3jAyMoKGhgasrKzq/G8PHjzIOGHv1KkTjhw5woRFRkaCy+Wy\nnplqb0nfuHEjLCwsoKamho4dO+LBgwf11m/YsGGsfFRUVNClSxdW/T/77DPGoXVNq8CJiYkYMmQI\ndHV1X8r40LsKnaRRKA1w/PhxFBcXM5+wsLC3LRKFwiIsLIz5f1Yr4zt37mD69OnYs2cPMjMzoaqq\nWsfEcX3pAKBTp044c+YM8vPzIZVK0b59e3z11VdMeHBwMJKSkpCamooLFy5g9erVOH36NICqswIL\nFy7E0aNHkZubCwsLC3h6ejZZh5kzZ8LOzq7esMuXL9drXtnPzw/6+vp4+vQpEhIScPHixUbNNFMo\nL4NcLsfGjRtfKw9CCCorK1tIIgrlfzQ0/uXn58PZ2Rn3799HZmYmPvnkE9bZxJUrV+LPP/9EYmIi\nHjx4gL///huhoaFM+IIFC5CSkoLCwkIcO3YMixYtwl9//QUAyMjIgLe3N9atW4fCwkL88MMP8PLy\nYrmj6NOnD+uZqeaLjYiICPznP//ByZMnUVxcjBMnTjDuO2oTExPDyqdv376ss2aenp7o0aMHcnJy\nsGzZMri6uuL58+cAAGVlZbi5ueE///lPi7T1W6c1nLG9Dx9QJ42UGtR0zFuT5ORk8tlnnxFtbW2i\no6NDvLy8SF5eHhO+cuVKYmxsTNTV1YmVlRU5f/48iYmJIcrKyoTH4xE1NTXStWtXQggh9vb2JDw8\nnBBS5fy0X79+ZN68eUQsFhNzc3Ny6tQpJt9Hjx6RAQMGEHV1dfL5558TPz8/Mn78+DdSd9oX3g9q\n/n9qsmDBAuLp6clcJycnE2VlZVJYWNhoutrIZDIyf/580rFjR+aesbExOXPmDHO9aNEi4u7uTggh\nZN68ecTPz48Jy8jIIABIcnJyg2VER0eTcePGkaCgoDr/54qKCtK9e3dy69atOs6Ira2tycmTJ5nr\nb775hkybNq3JOr0KtD98XEgkErJixQqipaXFjO3h4eHE3t6eEELIlStXiK2tLdHQ0CC2trbkypUr\nTFp7e3uycOFC0rdvXyIQCIiXlxdRUlIifD6fqKmpkZkzZxJCqv5TW7duJe3atSNisZj4+fkxDn2r\ndUE1jcWVy+Vk7ty5REdHh5ibm5PNmzczzoDfBLQvvBs0d/zLyckhAEh2djYhhJBevXqRgwcPMuH7\n9u0jpqam9ZZx7949YmhoSA4cOEAIIeT69etET0+PFUdXV5dcvXqVEFL3f1sThUJBTE1NWU7Xm8vj\nx4+JkpISefToESGEkPv37xMVFRVGnxFCSP/+/cnWrVtZ6ZKSkt7o/xXUmTWF8u5BCMGCBQsglUrx\nzz//ID09HcHBwQCA+/fvIywsDDdu3EBRURHOnDkDc3NzDB06lDH/X1xcXMePUDXx8fHo0KEDsrOz\n8d1332Hy5MnM/n8vLy988sknyMnJQXBwMPbs2dNaVaa8wyxYsAC6urro168fs7Xkzp07LJ9hlpaW\nUFFRYW0tqS9dNWlpaRCLxRAKhVizZg2+++47AEBeXh6kUikr727dujGWt6qVSjXV32tbjKymsLAQ\ngYGBWLt2bb3h69evx8CBA+v4TgOqLNrt37+fcVQaExPDmPenUF4XW1tbODg4YM2aNaz7ubm5GDFi\nBP7v//4POTk5mDt3LkaMGIGcnBwmzp49e7Bjxw4UFRUhMjISAwYMYFaua+7GOHHiBG7cuIFbt27h\n4MGDOHPmTIPyNBQ3PDwcMTExSEhIwN9//83afkb5cGnu+Hfp0iUYGhpCR0cHQP1j9JMnT1juMfz8\n/JhthEZGRhg+fDiAqj7RsWNHHDt2DAqFAkeOHAGfz2eNzzdv3oSuri6srKywdOlSZgv6kydP8OTJ\nEyQmJsLMzAwWFhYICgpq1krz7t27MWDAAFhYWACo0m9t27aFSCRi4tTUQx8adJJGoTSAi4sLxGIx\n8wkPD0e7du3wxRdfgM/nQ09PD3PnzmVMwnK5XJSVleHu3buoqKiAubk5LC0tm12eRCLB1KlTweVy\n4ePjg6dPnyIzMxNpaWm4ceMGlixZAhUVFfTv3/+1TDZTPgxWrVqFR48eISMjA9OmTcPIkSPx8OFD\nFBcXQ1NTkxVXU1MTRUVFjaarpk2bNsjPz0d2djZCQ0NhbW0NACguLmbyqi/f4cOH4+DBg7h9+zZK\nS0uxZMkScDgclJSU1Cv/4sWLMXnyZJiZmdUJS09Px/bt27FkyZJ609rb2+POnTvQ0NCAqakpbG1t\n4eLi0tymo1CaZMmSJdi8eTOzjQoATp48ifbt2+PLL78Ej8eDp6cnrK2tcfz4cSbOxIkTYWNjAx6P\nB2Vl5Qbznz9/PsRiMdq0aYPPPvusjoP55sQ9ePAgZs2axfiNmj9/fgvUnPKu05zx78mTJ5g5cybr\n3PCwYcOwceNGPH/+HM+ePcOmTZsAgDVGb9myBUVFRYiLi8OYMWPA5/MBVD3fTJgwAV5eXuDz+fDy\n8sL27duhpqYGABg4cCASExORlZWFX375BdHR0fjhhx8YWQDg7Nmz+O9//4sLFy4gOjq6WVsSd+/e\njYkTJzLXTem3Dw06SaNQGuDIkSPIz89nPlOnTkVWVhY8PDxgYmICDQ0NeHt7Izs7GwDQrl07bNiw\nAcHBwdDX14eHh0ezDCdUY2hoyHxXVVUFUDUgSaVSaGtrM/cA1PtgS/m46N27N0QiEfh8Pnx8fNCv\nXz+cOnUK6urqKCwsZMUtLCxk3jw2lK422tra8PHxwahRoyCXyxkn1TXzrpnv559/jpCQEIwdOxYS\niQTm5uYQiUQwNTWtk3dCQgLOnz+POXPm1Fu32bNnIzAwsI4yBoDKykoMGTIEY8aMwYsXL5CdnY28\nvLzX8l1FodSmc+fOcHJywsqVK5l7UqkUEomEFU8ikbCM6zR3bK493le/BHmZuFKplFUe1QsfPs0Z\n/54/fw5HR0f4+fmxzgUHBASgR48e6N69O/r27QsXFxcoKyvX8RvI5XLRv39/PHnyhPGref78eXz3\n3XeIjY1FeXk5Ll68iClTpjAvDNq2bQsLCwsoKSmhS5cuCAwMxKFDhwAAQqEQAPDdd99BLBbD3Nwc\n06dPr1fv1OTy5ct49uwZXF1dmXtN6bcPDTpJo1BeggULFoDD4eD27dsoLCzE3r17WdsHvLy8cPny\nZaSmpoLD4TAD5+tYGTIyMkJubi7rbVe140cKpZpq89g2NjasLbWPHj1CWVkZrKysGk1XH3K5HFlZ\nWSgsLISWlhaMjIxYed+6dQs2NjbM9cyZM5GUlISsrCyMHTsWcrkcnTt3rpNvbGwsUlJS0KZNGxga\nGmLNmjX45Zdf0LNnTwDAb7/9hm+//RaGhobMA2qfPn0QFRWF3NxcpKenw9/fH3w+Hzo6OvD19W1S\n4VMoL0tISAjCw8OZSZixsTFSU1NZcdLS0mBiYsJc1x7r36SFOSMjI2aVAqB64WOgqfEvLy8Pjo6O\ncHZ2RkBAACutUChEWFgYMjIy8OjRI+jo6KBXr17gcut39yWXy5ldFgkJCRg4cCBsbW2hpKQEOzs7\n9O7dm2VZsSY19UqHDh2goqLy0n1h165dGDNmDPOCEABsbGzw6NEj1spZbT30IUEnaRTKS1BUVAR1\ndXWIxWJkZGQwy/lA1Zm033//HWVlZRAIBBAKhczgZ2BggJSUlFey9iWRSGBra4vg4GCUl5fj2rVr\nrO01lI+P/Px8nDlzBjKZDHK5HPv27cOlS5cwZMgQjB8/HsePH0dcXBxevHiBwMBAjBkzBiKRqNF0\nAHD48GHcv38flZWVeP78OebOnYsePXpAW1sbADBhwgSEhoYiLy8P9+7dQ3h4OLMVRSaTITExEYQQ\npKWlYdq0aZg1axa0tLTqyD9t2jQ8fPgQCQkJSEhIwIwZMzBixAjmrM2DBw9w69YtJhyosrY6evRo\n6OrqwsLCAlu3boVcLkd+fj527drFOitHobQE7dq1g7u7O7MtbPjw4Xjw4AGioqIgl8tx4MAB3L17\nF05OTg3mYWBggEePHr0R+dzc3LBx40ZkZGQgPz8fq1ateiPlUN4dGhv/CgsLMWTIEPTr14+1AlxN\nRkYGpFIpCCG4fv06li5dipCQEABAVlYW9u/fj+LiYigUCpw5cwbR0dEYNGgQAMDOzg5xcXHMeHzz\n5k3ExcUxZ9JiYmKQmZkJALh37x6WLl3KWJZUVVWFu7s7Vq9ejaKiIjx58gTh4eGN9pvS0lL8/PPP\nrK2OAGBlZYXu3bsjJCQEMpkMv/76K27fvo2xY8cCqDpnJ5PJUF5eDqBKL5WVlb1qc799WsM6yfvw\nAbVaRKmBRCIhAoGAqKmpMR8XFxeSmJhIevbsSdTU1Ei3bt3ImjVriImJCSGEkFu3bhE7Ozuirq5O\ntLS0yIgRI0hGRgYhhJDs7GzSr18/IhaLSY8ePQgh9Vt3rAlqWLRLTk4m/fv3J+rq6mTQoEFk6tSp\nZNKkSW+k7rQvvPtkZWURW1tboq6uTjQ1NUnv3r3J2bNnmfB9+/YRMzMzoqqqSpydnUlOTk6z0m3a\ntImYm5sTVVVVYmBgQNzd3UlKSgoTLpPJiK+vLxGJRERfX5+sXbuWCcvLyyNdunRh0s6fP5/I5XIm\nfNmyZWTo0KH11qc+6441QS3rjjdv3iT29vZELBYTHR0d4urqSjIzM1+iBZsP7Q8fF7Ut+6alpRE+\nn89Yd4yLiyM9e/YkGhoapGfPniQuLo6JW5/l1KtXr5L27dsTsVhMvv76a0JI3f+zj48PCQgIIITU\nb92xobgVFRVk9uzZRFtbm5ibm5N169YRHo/HWH9saWhfeDdoaPyLjIwkAIiqqirr2SU1NZUQQsjF\nixeJRCIhQqGQWFlZkb179zJ5ZmVlkYEDBxJNTU0iEolI586dyY4dO1jlbt68mVhaWhJ1dXViYWFB\n1qxZw4TNmzeP6OvrE1VVVWJhYUEWL15MysvLmfCCggLi7u5O1NXViampKQkJCWH+p5cuXSJqamqs\nsqKiokibNm3q/S8/fvyY2NvbE4FAQKysrFj99fHjxwQA6yORSF69sRsArWTdkUMa2ObyscHhcAht\nC8r7gru7O6ytrZm3YC1JY9vfKJSPDdofKO8LMTExmDFjRp0tmS0F7QsUShX/9oU37i2bTtL+RSgU\nKmQyGd3+SfnoEQgEkMlkb1sMCuWdgPYHCqUK2hcolCoEAkFlaWlp/Yf5WhA6SfsXupJGoVRB35ZS\nKP+D9oeXIzg4GMnJydi7d2+L5hsXF4cpU6bg/v37LZrv22bYsGHw8PCAj49Pi+Tn4OAAb29vTJky\npUXyqwntCxRKFa21kkZXjih1MDc3b9BiT3NISUkBh8NhHBm2Jurq6m/skDaFQgHCwsJga2sLPp9f\n51B3SUkJ/Pz8oKurC01NTQwcOLDJ/JKSkiAQCODt7c3cI4Rg2bJlaNOmDTQ0NODh4VHH7DJQZelM\nT08P/fv3f+16Udi8rh54XTgcDpKTk5nrAQMGfHATNKBqi2JLTdAolI+dxvTT+widpL0l9u/fj969\ne0NNTQ36+vro3bs3tmzZQt9SvQQODg6IiIhg3SsuLkbbtm3fkkT1QwhB27Zt0alTpzph9dUhNjaW\n5VvKwcEBAoEAIpEIGhoa6NWrF1auXPl+WyyivLcYGxtj0aJFmDRpUp2wadOmITc3F//88w9yc3Ox\nfv36JvObOXMm7OzsWPd2796NPXv24MqVK5BKpSgtLcXXX39dJ+3333+Pjh07vnplKJR3mLfxopNC\neZ9pTD+9j9BJ2ltg7dq1mDVrFr799ls8e/YMmZmZ2LZtG65cucKYDa2JQqF4C1JSWopLly4hKysL\njx49wo0bN14pj7CwMBQVFeHp06dYu3Yt9u/fj+HDh9NJPaXVGTNmDFxcXKCjo8O6f//+fRw7dgw7\nduyAnp4euFwuevXq1Whe+/fvh1gsxueff866f/z4cUyePBlmZmZQV1fH999/jwMHDrB8BV67dg2J\niYnw9fVtucpR6hAZGYn+/fvjm2++gZaWFiwsLBATE8OEP378GPb29hCJRPjiiy+QnZ3NhNV+4QSw\nV+gUCgWWL18OS0tLiEQi9OrVC+np6cwKbLdu3aCuro4DBw7Uyeuff/6Bg4MDxGIxbGxscOzYMSZs\n4sSJmDlzJkaMGAGRSITevXsz/p4aY9asWTAzM2NehsXFxTFhDckKAOfOnYO1tTU0NTXh7+8Pe3t7\n5uVbcHAwa5W49k6Tmi/qIiMj0a9fP8yZMwfa2toIDg4GAPz000/o2LEjtLS0MGTIEJZhkNplU51A\n+ZhpSD+9r9BJWitTUFCAwMBAbNmyBa6urhCJROBwOOjRowf27dvHLNF+9dVXGD58ONTU1HDhwgUU\nFBRgwoQJ0NPTg0QiQWhoKONzqzlKYPHixejXrx9EIhEcHR1ZinTPnj2QSCTQ0dHBsmXLmlWPyspK\nrFy5EpaWltDR0YGbmxtyc3MbrPPkyZNhZGQEExMTLFq0CAqFAmVlZRCLxUhMTGTiPn/+HEKhEFlZ\nWcjLy4OTkxP0UWnOVQAAIABJREFU9PSgpaUFJycnxnFnQEAA4uLi4O/vD3V1dfj7+wNgb5FprM2a\nevBoCAcHByxatAh9+/aFuro6Ro4ciZycHIwfPx4aGhqws7NDSkoKK82uXbswatQoDB8+HLt27WpW\n+zaEmpoaHBwccOzYMVy7dg0nT558rfwolJYiPj4eEokEQUFB0NXVRZcuXfDLL780GL+wsBCBgYFY\nu3ZtnbBq88M1r8vKypCUlASg6oF55syZCAsLe6POgilVxMfHo0OHDsjOzsZ3332HyZMnM7+Pl5cX\nevXqhezsbCxevPilxrh169YhOjoap06dQmFhIX766Seoqqri0qVLAKqc1BYXF8Pd3Z2VrqKiAiNH\njoSjoyOysrKwefNmjB8/nrUdMjo6GkFBQcjLy0O7du3qOPatDzs7OyQkJCA3NxdeXl4YN24cYyij\nIVmzs7MxduxYhIaGIjs7G5aWlrhy5Uqz26A28fHxaNu2LbKyshAQEIAjR45g+fLlOHz4MJ4/f44B\nAwbA09MTAFq8bAqF8m5BJ2mtzLVr11BWVsY4+WuIqKgoBAQEoKioCP3798fXX3+NgoICPHr0CBcv\nXsTu3buxc+fOZpcbFRWFnTt3IisrC+Xl5VizZg0A4O7du/jqq6+wZ88eSKVS5OTkMBOhxti0aROO\nHDmCixcvQiqVQktLCzNnzqw3ro+PD3g8HpKTk3Hz5k2cPXsWERER4PP5GDNmDKKjo5m4Bw8ehL29\nPfT19VFZWQlfX1+kpqYiLS0NQqGQmYwtW7YMAwYMQFhYGIqLixEWFlan3KbarLEHj8bYv38/9uzZ\ng4yMDDx8+BB9+vSBr68vcnNz0bFjR5ZZ/JKSEhw6dAjjx4/H+PHjsX///npXS1+WNm3awNbWlvWm\nl0J5mzx58gSJiYnQ1NSEVCpFWFgYfHx88M8//9Qbf/HixcxqWW2GDRuGiIgIpKSkoKCggHHSW72S\ntmnTJvTu3bvJlTpKyyCRSDB16lRwuVz4+Pjg6dOnyMzMRFpaGm7cuIGlS5eCz+dj4MCBGDlyZLPz\njYiIQGhoKDp06AAOh4Nu3bo16w349evXUVxcjPnz50NFRQWDBg2Ck5MTS5eMGTMGn3zyCXg8HsaP\nH8844W0Mb29v6OjogMfjYd68eSgrK2Mmfg3JeurUKXTq1Amurq5QVlbG7NmzYWho2Ow2qI2xsTG+\n/vpr8Hg8CIVCbN++HQsWLEDHjh3B4/GwcOFCJCQkIDU1tcXLplAo7xZ0ktbKZGdnQ1dXFzwej7nX\nt29fiMViCIVC5g3iqFGj0K9fPygpKUFZWRkHDhzAihUrIBKJYG5ujnnz5mHPnj3NLtfX1xdWVlYQ\nCoVwc3NjFNahQ4fg5OSEgQMHgs/nY+nSpVBSavpvsX37dixbtgympqbg8/kIDg7GoUOH6uyhz8zM\nRExMDDZs2MCcv5szZw72798PoOotbE3FGhUVBS8vLwCAjo4Oxo4dC1VVVYhEIgQEBODixYvNqq9C\noWiyzRp68GgKX19fWFpaQlNTE8OGDYOlpSUGDx4MHo+HcePG4ebNm0zcw4cPg8/nw9HREU5OTpDL\n5XVWv/7v//4PYrGY+Tg5OTWrjsbGxg2uXlIorY1QKISysjIWLVoEFRUV2Nvb47PPPsPZs2frxE1I\nSMD58+cxZ86cevOaNGkSPD094eDgABsbG3z22WcAAFNTU0ilUmzatKnZq/6U16fmg7+qqiqAqvO/\n1S/o1NTUmHCJRNLsfNPT02FpafnS8kilUpiZmbF0lUQiQUZGRoMyFxcXN5nv2rVr0bFjR2hqakIs\nFqOgoIDZddKQrNWyVMPhcOp98dBcaqdNTU3FrFmzGP2gra0NQggyMjJavGwKhfJuwWs6CqUl0dHR\nQXZ2NuRyOTNRu3r1KoCqB5Dq7Xg1B9rs7GyUl5ezlF9thdQUDSms2oO8mppas95kpqamYvTo0Swl\nyeVy60xyUlNTUVFRASMjI+ZeZWUlU+agQYNQWlqK+Ph4GBoaIiEhAaNHjwZQ9dZ8zpw5OH36NPLy\n8gAARUVFUCgU4HIbd0/RnDZr6MGjKQwMDJjvQqGwznXNPHbt2gU3NzfweDzweDyMGTMGu3btYuoI\nVK0K1DSXHBsby9q+2hAZGRno27dvk/EolNaga9euzY4bGxuLlJQUtGnTBkBVv1MoFLh79y7+/vtv\nKCkpISQkhFmVPnv2LExMTGBiYoJjx47h6dOnjCGe0tJSlJaWwtDQEBkZGU2ODZSWw8jICHl5eXjx\n4gUzUUtLS2O2oKqpqbHOESoUCjx//py5NjMzw8OHD9G5c+eXKtfY2Bjp6emorKxkdFBaWhqsrKxe\nuS5xcXFYtWoVfvvtN9jY2EBJSQlaWlrM7oqGZDUyMmLOpgFVW3NrXtdug2fPnjUqR+3tu2ZmZggI\nCMD48ePrxE1KSmq0bAqF8n5DV9JamT59+oDP5+Po0aONxqs5UOvq6kJZWZl1WDgtLQ0mJiYAXl4J\n1KS2gikpKUFOTk6T6czMzBATE4P8/HzmI5PJGJlqxuPz+cjOzmbiFRYW4s6dOwAAJSUluLm5ITo6\nGlFRUXBycoJIJAJQ9Vbz/v37iI+PR2FhIbPKWK00GzuL0lSbtQZPnjzB77//jr1798LQ0BCGhoY4\ndOgQTp06xToT+Cqkp6fjr7/+woABA1pIWgqlecjlcshkMigUCigUCshkMsjlcgwcOBBt2rTBihUr\nIJfLceXKFcTGxmLIkCF18pg2bRoePnyIhIQEJCQkYMaMGRgxYgTOnDkDoMq0/sOHD0EIwd27dzF3\n7lwEBgZCSUkJw4YNQ0pKCpN2yZIl6NGjBxISEugErZWRSCSwtbVFUFAQysvLcfnyZRw/fpwJt7Ky\ngkwmw8mTJ1FRUYHQ0FCWVdopU6Zg8eLFSEpKAiEEt2/fZvSPgYFBg+5Uqi0jr169GhUVFYiNjcXx\n48fh4eHxynUpKioCj8eDnp4e5HI5lixZwnL70JCsI0aMwJ07d3D48GHI5XJs2rSJpYO7d++OS5cu\nIS0tDQUFBVixYsVLyTVjxgysWLGC0ZkFBQX4+eefAaDJsimUj42G9NP7Cp2ktTJisRhBQUHw8/PD\noUOHUFxcjMrKSiQkJODFixf1puFyuXBzc2POqKWmpmLdunXMasvrKAFXV1ecOHECly9fRnl5OQID\nA5nVvMaYMWMGAgICmEnQ8+fP6514GhkZwdHREfPmzUNhYSEqKyvx8OFD1rZFLy8vHDhwAPv27WO2\nOgJVSlMoFEIsFiM3N5d11gtoXIk31WatwZ49e2BlZYX79+8zD5QPHjyAqakpa4vny1BSUoKLFy9i\n1KhR+OSTTzB8+PAWlppCaZzQ0FAIhUKsXLkSe/fuhVAoRGhoKJSVlXH06FGcOnUKmpqamDp1Knbv\n3g1ra2sAwPLlyzFs2DAAVSvX1S8uDA0Noa6uDoFAAD09PQBVK+HVhpOGDRuGSZMmYdq0aQAAPp/P\nSqupqQllZWV6FuctERUVhfj4eGhrayMkJAQTJkxgwjQ1NbFlyxZMmTIFJiYmUFNTY1lonDt3Ltzc\n3ODo6AgNDQ1MnjwZpaWlAKoMYvn4+EAsFuPgwYOsMlVUVHDs2DHExMRAV1cXfn5+rP/aqzBkyBAM\nGzYMVlZWkEgkEAgErF0mDcmqq6uLn3/+GfPnz4eOjg6SkpLQr18/Jt0XX3wBd3d3dO3aFb169Wr2\ndvZqRo8eje+//x4eHh7Q0NBA586dGSNXTZVNoXxsNKSf3luqrWh97J+qpmg99u7dS+zs7IhQKCS6\nurrkk08+Idu3bydlZWXEx8eHBAQEsOLn5uaS8ePHE11dXWJqakpCQkKIQqFgwv38/IimpiaxtLQk\nO3bsIABIRUUFIYQQe3t7Eh4ezsTduXMn6devH3MdGRlJzMzMiLa2NgkNDSUSiYScO3euUfkVCgVZ\nu3YtsbKyIurq6qRt27ZkwYIFhBBCHj9+zCo/Pz+fzJgxg5iYmBANDQ3SvXt3Eh0dzcrP0tKSaGlp\nkbKyMuZeRkYGsbe3J2pqaqR9+/Zk27ZtrHyvXr1K2rdvT8RiMfn6668JIYQAIElJSU22We02qJ22\nIWq3ZUBAAPHx8WGuz507RywtLQkhhHTo0IFs2rSpTh6rVq0ivXr1qjc/Qgi5cOECMTExYZXJ5/OJ\nuro6UVdXJ927dyehoaGktLS0UVlfldbuCxTKuwztD5SXpb5x/UOA9gUKpYp/+8Ibn5twCPWpAQAQ\nCoUKmUxGVxYpHz0CgYAxO02hfOzQ/kChVEH7AoVShUAgqCwtLX3j++vpJO1fOBwOoW1BeZPY2Njg\nxx9/hIODQ4vkZ25ujoiICAwePLhF8quGw+FQh6gUyr/Q/vBuUm1gqdplTEuPr63FjBkzYGJigsWL\nF7dIfhMnToSpqekb2eJF+wKFUsW/feGNO+mkK0eUZrF//37msLa+vj569+6NLVu20AH7Jbhz5857\n9wBBobyrhIWFwdbWFnw+HxMnTnzb4lBq4eDggIiIiFYr730dX7dt29ZiEzQK5WPnQ9MLdJJGaZK1\na9di1qxZ+Pbbb/Hs2TNkZmZi27ZtuHLlSos4ZqbgvbY+RKG8DYyNjbFo0SJMmjTpbYtCobwRqF6g\nUF6OD00v0EkapVEKCgoQGBiILVu2wNXVFSKRCBwOBz169MC+ffvA5/Nx8uRJ9OjRAxoaGjAzM0Nw\ncDCTPiUlBRwOBzt37oSZmRm0tLSwbds23LhxA127doVYLIa/vz8TPzIyEv369cOcOXMgFovRtm1b\nXL16FZGRkTAzM4O+vj527drFxG+s7MYYN24cYxlu4MCBjHljoMrv0rx58yCRSKCpqYn+/fszFsf2\n7NkDiUQCHR0dLFu2DObm5jh//jyAqm0mixYtYvKJjY1lWTKrGTc4OBiurq7w9vaGhoYGIiMjUVlZ\niZUrV8LS0hI6Ojpwc3NjOauuXTaF8jEzZswYuLi4NMuvI+XtkZeXBycnJ+jp6UFLSwtOTk7MFsX9\n+/fD1taWFX/9+vVwdnYGAJSVleGbb75BmzZtYGBggBkzZjBjcW1qj69ubm6YMGECRCIRbGxs8Oef\nfzYpa/X4KxKJ0KlTJ/z666+s8PDwcHTs2JEJ//vvvwEAN2/eRM+ePSESieDu7g4PDw9GF0RGRqJ/\n//6sfDgcDpKTkwGw9Ua1zli1ahUMDQ3h6+sLADhx4gS6d+8OsViMvn374vbt20xetcumZ8YoHzMf\nml6gkzRKo1y7dg1lZWUYNWpUg3HU1NSwe/du5Ofn4+TJk9i6dSuOHDnCihMfH4+kpCQcOHAAs2fP\nxrJly3D+/HncuXMHBw8eZJnkj4+PR9euXZGTkwMvLy94eHjgxo0bSE5Oxt69e+Hv7884jG5O2fUx\nbNgwJCUlISsrCz179mQ5Cv3mm2/w119/4erVq8jNzcXq1auhpKSEu3fv4quvvsKePXsglUqRk5PD\nPGy8CkePHoWrqyvy8/Mxfvx4bNq0CUeOHMHFixchlUqhpaWFmTNnAkCLl02hUCitQWVlJXx9fZGa\nmoq0tDQIhULmxZyzszPu37+PpKQkJn5UVBTjiuX777/HgwcPkJCQgOTkZGRkZGDJkiXNKvfYsWPw\n8PBAfn4+nJ2dWS8DG8LS0hJxcXEoKChAUFAQvL298fTpUwDAzz//jODgYOzevRuFhYU4duwYdHR0\nUF5eDhcXF3z55ZfIzc3FuHHj8Msvv7xsMzE8e/YMubm5SE1NxY4dO/D3339j0qRJ2L59O3JycjB9\n+nQ4OzujrKysxcumUCjvFnSSRmmU7Oxs6OrqgsfjMff69u0LsVgMoVCIS5cuwcHBAV26dIGSkhK6\ndu0KT09P1qQLABYvXgyBQABHR0eoqanB09MT+vr6MDExwYABA3Dz5k0mroWFBXx9fcHlcuHu7o70\n9HQEBgaCz+fD0dERKioqzFvI5pRdH5MmTYJIJAKfz0dwcDBu3bqFgoICVFZW4qeffsLGjRthYmIC\nLpeLvn37gs/n49ChQ3BycsLAgQPB5/OxdOlSKCm9ehfq06cPXFxcoKSkBKFQiO3bt2PZsmUwNTVl\n5Dp06BDkcnmLl02hUCitgY6ODsaOHQtVVVWIRCIEBAQwY7SqqipGjRrF+I1MSkrCvXv34OzsDEII\nwsPDsX79emhra0MkEmHhwoXYv39/s8rt378/hg8fDi6Xiy+//BK3bt1qMs24ceNgbGwMJSUluLu7\no3379vjjjz8AABEREfjuu+9gZ2cHDoeDdu3aQSKR4Pr166ioqMDs2bOhrKwMV1dX2NnZvWJrAUpK\nSggJCQGfz4dQKER4eDimT5+O3r17g8vlwsfHB3w+H9evX2/xsikUyrsFfcqjNIqOjg6ys7NZe+Ov\nXr2K/Px86OjooLKyEvHx8fjss8+gp6cHTU1NbNu2DdnZ2ax8DAwMmO9CobDOdfXKWH1x67tXHb85\nZddGoVBg/vz5sLS0hIaGBszNzQFUTUizs7Mhk8lgaWlZJ51UKmU5N1VTU3utJfWaeQFAamoqRo8e\nDbFYDLFYjI4dO4LL5SIzM7PFy6ZQKJTWoKSkBNOnT4dEIoGGhgYGDhyI/Px8KBQKAICXlxczSYuK\nioKLiwtUVVXx/PlzlJSUoFevXsyYOHToUDx//rxZ5dZ0bq6qqgqZTNbkGa/du3cz2wrFYjESExMZ\nfZKent6gXjAxMQGH8z9DbxKJpFky1oeenh4EAgFznZqairVr1zIyicVipKenQyqVtnjZFArl3YJO\n0iiN0qdPH/D5fBw9erTBOF5eXnB2dkZ6ejoKCgowY8aMVrP6+CplR0VF4ejRozh//jwKCgqQkpIC\noMqxu66uLgQCAR4+fFgnnZGREdLT05nrkpIS5OTkMNdqamooKSlhrp89e9aoHDUVK1A1aYuJiUF+\nfj7zkclkMDExabJsCoVCeRdZu3Yt7t+/j/j4eBQWFuLSpUsAwIzTjo6OyM7ORkJCAqKjo5mtjrq6\nuhAKhbhz5w4zHhYUFLBe6LUkqampmDp1KsLCwpCTk4P8/Hx07tyZkdPMzKxBvZCRkcHSO2lpacz3\nltALAQEBLL1QUlICT0/PJsumUCjvN3SSRmkUsViMoKAg+Pn54dChQyguLkZlZSUSEhLw4sULAEBR\nURG0tbUhEAjwxx9/ICoqqtXke5Wyi4qKwOfzoaOjg5KSEixcuJAJU1JSwqRJkzB37lxIpVIoFArm\nXJ6rqytOnDiBy5cvo7y8HIGBgaisrGTSdu/eHadOnUJubi6ePXuGDRs2vFRdZsyYgYCAAKSmpgIA\nnj9/zkyOmyqbQvnYkMvlkMlkUCgUUCgUzVopobQ+RUVFEAqFEIvFyM3NRUhICCucx+PB1dUV3377\nLXJzc/HFF18AqBqLp06dijlz5iArKwsAkJGRgTNnzrwROV+8eAEOhwM9PT0AwM6dO5GYmMiET5ky\nBWvWrMFff/0FQgiSk5ORmpqKPn36gMfjYdOmTZDL5Th8+DCzRRIAunXrhjt37iAhIQEymazZxq2q\nmTp1KrZt24b4+HgQQvDixQucPHkSRUVFTZZNoXxsfGh6gU7SKE3y3XffYd26dVi9ejX09fVhYGCA\n6dOnY9WqVejbty+2bNmCwMBAiEQiLFmyBG5ubq0m26uUPWHCBEgkEpiYmKBTp0749NNPWeFr1qxB\nly5dYGdnB21tbXz//feorKxknKV6eXnByMgIWlpaLOuNX375Jbp16wZzc3M4OjrC3d39peoya9Ys\nODs7w9HRESKRCJ9++ini4+MBoMmyKZSPjdDQUAiFQqxcuRJ79+6FUCh8Iw58Ka8Oh8PB7NmzUVpa\nCl1dXXz66acYOnRonXheXl44f/48xo0bxzr/vGrVKrRr1w6ffvopNDQ0MHjwYNy/f/+NyNqpUyfM\nmzcPffr0gYGBAf773/+iX79+TPi4ceMQEBAALy8viEQiuLi4IDc3FyoqKjh8+DAiIyOhpaWFAwcO\nYMyYMUw6KysrBAYGYvDgwWjfvn0dS49NYWtri/DwcPj7+0NLSwvt2rVDZGQkADRZNoXysfGh6QUO\ndUZcBYfDIbQtKC+Lubk5IiIiMHjw4LctSovB4XCok3IK5V9of3g1evbsicDAQLi4uLxtUVqdiRMn\nwtTU9L1+OKwP2hcolCr+7QucpmO+Zjm0w1UhFAoVMpmMrixSPnoEAgH1tUOh/AvtDxRKFbQvUChV\nCASCytLSUu6bLodO0v6ltVbSHBwc4O3tjSlTprzxst5X4uLiMGXKlBbb1hIbGwtvb2/qV6yZ0Lel\nFMr/aOn+QHVA03wMOiA4OJjx/Vkf1VvcHRwcWlewRqC6gUKporVW0ujK0Stgbm6O8+fPs+5FRka+\n9F5zSv0MGDDgjZ07oFAoHwZhYWGwtbUFn8/HxIkTW7VsqgPeLFQHAHfu3HmnJmgUyvtCbm4uRo8e\nDTU1NUgkklY1ZtfS8JqOQvnQkcvlrMPa7zLvk6wtxcdYZwqlKYyNjbFo0SKcOXMGpaWlb1uc95r3\naYx5n2SlUCitz8yZM6GiooLMzEwkJCRgxIgR6NatG2xsbN62aC8NXUlrYX744QeMHTuWde/rr7/G\n7Nmz68StrKxEaGgoJBIJ9PX1MWHCBBQUFDDhu3fvhkQigY6ODpYuXcp6e1taWgofHx9oaWmhY8eO\nWL16Ncvan1QqxdixY6GnpwcLCwts2rSJCQsODoarqyu8vb2hoaHBWIqqjz/++AN9+vSBWCyGkZER\n/P39UV5ezoTfuXMHX3zxBbS1tWFgYIDly5cz8k2cOBFaWlro1KkTfvjhB5Z8HA4HycnJzPXEiROx\naNEiAFVbU2rGNTc3x6pVq9C1a1eoqalBLpc3Wr/aZd+4caPB+tXkn3/+gYODA8RiMWxsbHDs2DGW\nfDNnzsSIESMgEonQu3fven3m1Kah9ikrK8Ps2bNhbGwMY2NjzJ49G2VlZaz6r1q1CoaGhvD19QUA\nnDhxgnG02rdvX9y+fbtZ9aJQPkTGjBkDFxeXd86pO9UBVAfUpKH2AYDy8nJMmDABIpEINjY2+PPP\nP1l1rv6tq38vd3d3iEQi9OzZE7du3WLirlq1CiYmJhCJROjQoQN+++23ZtWXQvnQePHiBX755Rcs\nXboU6urq6N+/P5ydnbFnz563LdorQSdpLYy3tzdOnz6N/Px8AFVv/Q4cOIAvv/yyTtzIyEhERkbi\nwoULePToEYqLi+Hv7w8AuHv3Lvz8/LBv3z48ffoUBQUFyMjIYNKGhIQgJSUFjx49wrlz51j72isr\nKzFy5Eh069YNGRkZ+O2337BhwwaWf5mjR4/C1dUV+fn5GD9+fIP14XK5WL9+PbKzs3Ht2jX89ttv\n2LJlC4Aq/zeDBw/G0KFDIZVKkZycjM8//5yR7+HDh3j48CHOnDmDXbt2vUarAtHR0Th58iTy8/Oh\npKTUaP1epeyKigqMHDkSjo6OyMrKwubNmzF+/HjWlpvo6GgEBQUhLy8P7dq1Q0BAQKN5NtY+y5Yt\nw/Xr15GQkIBbt27hjz/+YFkCe/bsGXJzc5GamoodO3bg77//xqRJk7B9+3bk5ORg+vTpcHZ2ZiZ2\nFArl3YDqAKoDqmmsfQDg2LFj8PDwQH5+PpydnZnfvj6OHj2KcePGITc3F15eXnBxcUFFRQXu37+P\nsLAw3LhxA0VFRThz5gzMzc2brC+F8iHy4MEDcLlcWFlZMfeqfRW+lxBC6KfqICxpLhKJhKipqRFN\nTU3mIxQKSb9+/QghhAwdOpTs2LGDEELI8ePHSceOHZm09vb2JDw8nBBCyKBBg8iPP/7IhN27d4/w\neDxSUVFBQkJCiIeHBxP24sULoqysTM6dO0cIIcTCwoKcPn2aCQ8PDycmJiaEEEKuX79OzMzMWDIv\nX76cTJw4kRBCSFBQEBkwYECz61uT9evXExcXF0IIIVFRUaR79+71xrOwsCAxMTHM9fbt2xn5CCEE\nAElKSmKufXx8SEBAACGEkAsXLrDiSiQS8p///Ie5bqp+TZVdH5cuXSIGBgZEoVAw9zw8PEhQUBAj\n3+TJk5mwkydPkg4dOjSaZ2Pt07ZtW3Ly5Enm+vTp00QikRBCquqvrKxMSktLmfAZM2aQRYsWsfKw\nsrIisbGxjcrwKrxMX6BQ3jYBAQHEx8fnjeVfX3+gOoDqgNfVAUFBQeTzzz9nru/cuUMEAgFzLZFI\nmN86KCiI9O7dmwlTKBTE0NCQXLp0iSQlJRE9PT1y7tw5Ul5e3qg8rwvVDZR3nep+XJMdO3YQe3v7\nFi3n377wxucmdCXtFTly5Ajy8/OZT/WbRQDw8fFh3mru3bu33jeoQNV2FIlEwlxLJBLI5XJkZmZC\nKpXCzMyMCVNVVWVt66kdXvN7amoqpFIpxGIx81m+fDkyMzPrjd8YDx48gJOTEwwNDaGhoYGFCxci\nOzsbAJCeng5LS8sG61azjJr1fBVepn6vUnZ1GiWl/3UJiUTCenNtaGjIfFdVVUVxcXGjeTbVPrV/\ne6lUylzr6elBIBAw16mpqVi7di2rzunp6aw0FAql9aA6gOqA19EB9eUnk8kgl8vrjVuzPkpKSjA1\nNYVUKkW7du2wYcMGBAcHQ19fHx4eHlQvUD5a1NXVUVhYyLpXWFgIkUj0liR6Pegk7Q3g4uKC27dv\nIzExESdOnGhwK4mxsTFSU1OZ67S0NPB4PBgYGMDIyIhlLri0tBQ5OTnMde3w9PR05ruZmRksLCxY\nDxBFRUU4deoUE4fDaZ7l0K+++grW1tZISkpCYWEhli9fzpjgNTMza3BPvpGREUumtLQ0VriqqipK\nSkqY62fPnjUqR015m6pfU2XXh7GxMdLT01FZWclKZ2Ji0mTahmisfer77Y2NjZnr2r+PmZkZAgIC\nWHUuKSmBp6fnK8tHoVDeDFQHUB1QLWdzzq01h5r1qaysxJMnTxid4eXlhcuXLyM1NRUcDgfff/99\ni5RJobw+cQ3kAAAgAElEQVRvWFlZQS6XIykpibl369at99JoCEAnaW8EgUAAV1dXeHl54ZNPPkGb\nNm3qjefp6Yn169fj8ePHKC4uxsKFC+Hu7g4ejwdXV1ccP34cV69eRXl5OYKCglj+Sdzc3LBixQrk\n5eUhIyMDYWFhTNgnn3wCDQ0NrFq1CqWlpVAoFEhMTGz24emaFBUVQUNDA+rq6rh37x62bt3KhDk5\nOeHZs2fYsGEDysrKUFRUhPj4+DryPXnyBJs3b2bl2717d0RFRUGhUOD06dO4ePFis2Vqqn5NlV0f\nvXv3hpqaGlavXo2KigrExsbi+PHj8PDwaLZctWmsfTw9PREaGornz58jOzsbS5Ysgbe3d4N5TZ06\nFdu2bUN8fDwIIXjx4gVOnjyJoqKiV5aPQnmfkcvlkMlkUCgUUCgUja5CtDZUB1AdADTePi/LX3/9\nhcOHD0Mul2PDhg3g8/n49NNPcf/+ffz+++8oKyuDQCCAUCgEl/vGfexSKO8kampqGDNmDAIDA/Hi\nxQtcuXIFR48ebXA3w7sOnaS9IXx8fPDf//630T/GpEmT8OWXX2LgwIGwsLCAQCBglImNjQ02b94M\nDw8PGBkZQSQSQV9fH3w+HwAQGBgIU1NTWFhYYPDgwXB1dWXCuFwujh8/joSEBFhYWEBXVxdTpkxh\nWQ1rLmvWrEFUVBREIhGmTp0Kd3d3JkwkEuHcuXM4fvw4DA0N0b59e1y4cAEAEBQUBIlEAgsLCzg6\nOtZph40bN+L48eMQi8XYt28fXFxcmi1TU/Vrquz6UFFRwbFjxxATEwNdXV34+flh9+7dsLa2brZc\ntWmsfRYtWgRbW1t07doVXbp0Qc+ePRnLZvVha2uL8PBw+Pv7Q0tLC+3atWvUIhuF8qETGhoKoVCI\nlStXYu/evRAKhSzjO28bqgOoDmisfV6WUaNG4cCBA9DS0sKePXtw+PBhKCsro6ysDPPnz4euri4M\nDQ2RlZXFsiBJoXxsbNmyBaWlpdDX14enpye2bt363q6kcWq+mfuY4XA4pCXbIi0tDdbW1nj27Bk0\nNDReO7/i4mKIxWIkJSXBwsKiTvjWrVuxf//+l3ob2ZrExsbC29ubtT2H8m7C4XBAxwUKpYpX7Q9U\nB7ChOuDVCQ4ORnJyMsuC59uA6gYKpYp/+0Lz9oy/Tjm0w1UhFAoVMpmMrixSPnoEAgFkMtnbFoNC\neSeg/YFCqYL2BQqlCoFAUFlaWvrG9xXTSdq/tPRK2vtKXFwcpkyZwvINU5OUlBRYWFigoqICPB7v\npfL+UN+kDhs2DB4eHvDx8UFkZCQiIiJw+fLlJtM19XbU3NwcERERGDx4cEuL3Cj0bSmF8j9of6C8\nKdLS0tCpUycUFBS0yDmy19HPzYH2BQqlitZaSaMrRx8x5ubmOH/+POvegAEDWBO0+uJQ2MTExMDH\nx+dti0GhfFSEhYXB1tYWfD4fEydOfNviUOrB3NwcQqEQ6urqzKfaYfPTp08xefJk5rydtbU1goKC\n8OLFi1cuLzIyEv3/n737Dq+iSh84/j0QSCG9QAiEG4oiQQWpAQQiAopERDqh4/JbVllBLAhBQAQb\nVsRVF5WaUBYFREFXWJGINEsQ6aAkIVEhhDRIIOX8/pjJeG86RQjwfp7nPrl3Zs6Zc+dmyjunzJ13\nlliOyngeq1evHllZWTLQhxCXyfV2XpAgTQghxDUnKCiIqVOnMnr06KtdFFGGdevWkZWVZb3mzZtH\namoq7dq1Izs7m23btpGZmcmXX35JWlraZRuy/lqntXZ4HIAQonzX23lBgjThYPPmzdStWxeAYcOG\nkZCQwP3334+7uzsvv/yytVx0dDT16tXD39+f2bNnW9PPnTvHhAkTCAoKIigoiAkTJnDu3LkS17V/\n/37Cw8Px9vamadOmfPLJJ9a8U6dOcf/99+Pp6Unr1q2ZOnWqdYf0kUce4fHHH3fI6/777+eNN94o\n87u9+OKLNGzYEA8PD0JDQ1m9erVVZm9vb37++Wdr2ZMnT+Lq6sqJEyc4ffo0ERERBAQE4OPjQ0RE\nhEOTzfDwcN5///0S1zl+/HiCg4Px9PSkZcuWxMbGOszPyclh4MCBeHh40KJFC3bv3l1iPgUFBVb5\n/fz8GDBgAKmpqWV+XyGuZ3369KF3794OD3gW14bXXnsNDw8Pli5dSkhICGA8U+zNN9/k9ttvLzOt\nUoq5c+fSoEED/P39efLJJy9LMHP06FG6dOmCn58f/v7+DBkyhLS0NGt+YmIiffr0ISAgAD8/P6tG\nMD8/nyeeeAJ/f38aNGjA22+/jVLKehxE0Vq8GTNmWI9bOXbsmMOy4eHhREVF0aFDB9zc3Pjll19I\nT0+3ahzr1KnD1KlTyc/PL3Hdn3322SVvByGuZdfbeUGCNFGqJUuWUK9ePetO6FNPPWXN++abbzh4\n8CCbNm1i5syZ7N+/H4DZs2ezfft24uLi2L17Nzt37ixxWOzc3Fzuv/9+unfvzokTJ3jrrbcYMmSI\n1dTykUceoUaNGvz+++8sWrSIRYsWWWlHjBjBsmXLrBNzSkoKmzZtKvfBzg0bNiQ2Npb09HSmT5/O\n0KFD+e2333B2dqZPnz4sW7bMWnblypV07tyZmjVrUlBQwKhRo4iPjychIQFXV1frBF2e1q1bExcX\nR2pqKpGRkfTv39+h4/XatWvp37+/Nb93797k5uYWy2fu3LmsWbOGr7/+muTkZHx8fHjkkUcqVAYh\nhKhMNm7cSJ8+fahS5eIuQVavXs13333HDz/8wNq1a/nwww8vuUxaayZPnkxycjL79+8nMTGRGTNm\nAEYwFBERgc1m49ixYyQlJVnPT5s/fz6ffvopP/74I9999x2rVq26pHIsWbKEf//732RmZmKz2Rgx\nYgROTk4cOXKEH3/8kf/+97/WTcHLvW4hROUiQZq4KNOnT8fV1ZVmzZrRrFkzqwYoOjqaadOmUbNm\nTQICApg+fTpLliwpln779u1kZWXx9NNPU716dbp06UJERATLli0jPz+fjz76iGeffRY3NzdCQ0Md\n+ny1adMGLy8vNm3aBMDy5csJDw+nVq1aZZa5f//+BAUFUaVKFQYOHMhNN93Ezp07AYiMjHQI0mJi\nYoiMjATAz8+Pvn374ubmhoeHB1FRURUe5nro0KH4+fnh5OTE448/zrlz5xz6/LVs2ZJ+/fpRrVo1\nJk6cSE5ODtu3by+Wz3vvvcfs2bOpW7cuzs7OzJgxg1WrVlWah/cKIURJevfujbe3t/WaP38+p06d\nonbt2hed56RJk/D19aVevXpMmDDB4di9fft2h/V5e3uTkJBQbp6NGjWiW7duODs7ExAQwMSJE63j\n/M6dO0lOTmbOnDnUqFEDFxcXq2XHypUrmTBhAsHBwfj6+jJ58uSL/l4AI0eOpGnTpjg5OZGamsqG\nDRt44403qFGjBjVr1uSxxx5j+fLlf8m6hRCVy+Uf/kfcEAIDA633bm5uZGVlAZCcnIzNZrPm2Ww2\nkpOTi6VPTk4mODjY4U6qzWYjKSmJkydPkpeXR3BwsDXP/j0YtWlLly6lW7duLF26lPHjx5db5sWL\nF/Paa69x7NgxwHjuUEpKCgBdunQhOzubHTt2EBgYSFxcHA8++CAAZ8+e5bHHHuPzzz/n9OnTAGRm\nZpKfn19uh+9XX32V999/n+TkZJRSZGRkWOss+r2qVKlC3bp1S9xe8fHxPPjggw7bq2rVqvzxxx/U\nqVOn3O8uhBBXw5o1a4qNUPvBBx/w22+/XXSe9sfNoueYsLCwYqPrFjapLMuJEyd49NFHiY2NJTMz\nk4KCAnx8fACjqaPNZitxxMTCc5l9eS6FfV7x8fHk5uY6BLQFBQXWMpd73UKIykVq0kSZlLqwEUaD\ngoKIj4+3PickJBAUFFTicomJiQ59CRISEqhTpw4BAQE4OTk59PtKTEx0SD906FDWrl3L7t272b9/\nP7179y6zXPHx8YwZM4Z58+Zx6tQp0tLSuPXWW63hhKtUqcKAAQNYtmwZMTExRERE4OHhARiB1sGD\nB9mxYwcZGRls2bIFoNyhiGNjY3nppZdYuXIlp0+fJi0tDS8vL4d09t+roKCA48ePl7i9goOD2bBh\nA2lpadYrJydHAjQhxDWna9eurF69+qL7ktkfN0s7x1yoyZMno5Tip59+IiMjg6VLl1rH6uDgYBIS\nEkpsuVC7du1i5bFXo0YNzp49a33+/fffyyyH/Tk3ODgYZ2dnUlJSrON+RkYGe/furdC6hRDXNgnS\nbnC5ubnk5ORYr6InoVq1avHLL79UOL/Bgwcza9YsTp48SUpKCjNnzrQ6Sdtr27YtNWrU4OWXXyY3\nN5fNmzezbt06Bg0aRNWqVenTpw8zZszg7NmzHDhwgMWLFzukr1u3Lq1bt2bYsGH07dsXV1fXMst1\n5swZlFIEBAQAsGDBAoeBQsBo8rhixQqio6Otpo5g1Jq5urri7e1Namoqzz77bIW2RWZmJk5OTgQE\nBJCXl8fMmTPJyMhwWOb777/n448/Ji8vjzfeeANnZ2fCwsKK5TV27FiioqKsAPjkyZOsXbu2QuUQ\n4nqUl5dHTk4O+fn55Ofnl3j8EpXTxIkTycjIYMSIEdYxLSkpiYkTJ/LTTz+Vm37OnDmcPn2axMRE\n3nzzTQYOHHjJZcrMzMTd3R1vb2+SkpKYM2eONa9NmzbUrl2bp59+mjNnzpCTk8PWrVsBGDBgAHPn\nzuX48eOcPn2aF1980SHf5s2bs3z5cnJzcy+431jt2rXp3r07jz/+OBkZGRQUFHD06FGrGWZ56xbi\nRnO9nRckSLvB3Xfffbi6ulqvwo7ShSZPnsysWbPw9vbmlVdeKTe/qVOn0qpVK26//XZuu+02WrRo\nwdSpU4stV716dT755BM2bNiAv78/Dz/8MIsXL+aWW24BjGddpKenExgYyLBhwxg8eDDOzs4OeYwY\nMYI9e/YwbNiwcssVGhrK448/Trt27ahVqxZ79uyhQ4cODssUBo7Jycn06NHDmj5hwgSys7Px9/cn\nLCyMe++9t9z1Adxzzz306NGDm2++GZvNhouLS7Fmmw888AArVqzAx8eHJUuW8PHHH1OtWrVieY0f\nP55evXrRvXt3PDw8CAsLY8eOHRUqhxDXo1mzZuHq6sqLL77I0qVLcXV1LXGQInF1FY4OXPh68MEH\n8fX15dtvv6VatWq0bdsWDw8P7r77bry8vGjUqFG5eT7wwAO0bNmS5s2b07NnTx566KFLLuf06dP5\n4Ycf8PLyomfPnvTp08eaV7VqVdatW8eRI0eoV68edevWZcWKFQCMGTOGe+65h2bNmtGiRQuHdADP\nPfccR48excfHh+nTpzvcAKyIxYsXc/78eUJDQ/Hx8aFfv35WU9Hy1i3EjeZ6Oy8oeXq8QSmlZVtU\nXpMmTbJGeiy0ZcsWhg4dyrFjxy56lDBRnFKq3KacQtwoZH+oXJRSHD58uELB3NVw7Ngx6tevT25u\nbol92K5lsi8IYTD3hQvrD3Qx65EdzuDq6pqfk5MjV/rihufi4uLwmAAhbmSyPwhhkH1BCIOLi0tB\ndnZ22SPHXQYSpJmkJk0Ig9wtFeJPsj8IYZB9QQjDlapJk5ojIS6DHj16WE0xFy5caD1DpzwzZswo\ncWCVQiEhIWzcuPGylFGI68m8efNo1aoVzs7OjBw58moXR/yFxo4dy3PPPXe1i3HBYmNjady4sfX5\nQo7nSimOHDlS4rwLOccIcSO53s4LEqSJK+6bb76hffv2eHl54evrS4cOHdi1axfu7u7Ww6XBeDC2\nUqrYtMLBRcoLcK6kDRs2ODxwWwjx1woKCmLq1KmMHj36ahflqouJiaFVq1a4u7tTu3ZtevToUexZ\nYZfL5s2bqVu37l+SN5QcgLz77rs888wzf9k6/yodO3bk4MGDV7sYQtwwrrfzggRp4orKyMggIiKC\nf/7zn6SmppKUlMT06dNxdnamXbt21tDCYAwMcssttxSb1qlTp6tRdCFEJdKnTx969+6Nn5/f1S7K\nVfXaa68xYcIEpkyZwh9//EFCQgIPP/zwVX1Ex7U85LUQ4tp1vZ0XJEgTV9ShQ4cA43lqVatWxdXV\nle7du3P77bfTqVMn60HRYDQVmTRpUrFplxKkvfjiizRs2BAPDw9CQ0NZvXo1AOfOncPb29vh2Wkn\nT57E1dWVEydOcPr0aSIiIggICMDHx4eIiAiHh22Hh4fz/vvvl7jO8ePHExwcjKenJy1btiQ2NtZh\nfk5ODgMHDsTDw4MWLVqwe/fuEvMpKCiwyu/n58eAAQNITU296G0hhLi2paenM23aNN5++2369OlD\njRo1qFatGvfffz9z5szh3LlzTJgwgaCgIIKCgpgwYQLnzp0D/qwRe/XVV6lZsya1a9dmwYIFVt7r\n168nNDQUDw8P6tSpwyuvvMKZM2fo0aMHycnJ1pD6ycnJzJgxg379+jF06FA8PT1ZuHAhI0eOdHj8\nStEauMTERPr06UNAQAB+fn6MGzeO/fv3M3bsWLZt22Y9swwoltf8+fNp1KgRvr6+9OrVi+TkZGue\nUop3332Xm266CR8fHx555JFy+1EdPXqULl264Ofnh7+/P0OGDCEtLQ0wzhn9+vVzWH78+PE8+uij\ngPHMzSZNmuDh4UGDBg147733Sv3O9nbu3Em7du3w9vamdu3ajBs3jvPnzzsss379eho0aIC/vz9P\nPvlkqQ//PnDgAN26dcPX15fGjRuzcuXKMr+vEOLaIEGauKJuvvlmqlatyogRI9iwYQOnT5+25nXq\n1ImtW7dSUFBASkoKZ86cYcCAAezcudOaduDAgUsK0ho2bEhsbCzp6elMnz6doUOH8ttvv+Hs7Eyf\nPn1YtmyZtezKlSvp3LkzNWvWpKCggFGjRhEfH09CQgKurq6MGzeuQuts3bo1cXFxpKamEhkZSf/+\n/R1GyFq7di39+/e35vfu3Zvc3Nxi+cydO5c1a9bw9ddfk5ycbF2ACCFuTNu2bSMnJ4cHH3ywxPmz\nZ89m+/btxMXFsXv3bnbu3OnwzKDff/+d9PR0kpKS+OCDD3jkkUesY/JDDz3Ee++9R2ZmJj///DNd\nunShRo0abNiwgaCgILKyssjKyiIoKAgwjmP9+vUjLS2NIUOGlFnu/Px8IiIisNlsHDt2jKSkJAYN\nGkSTJk149913adeuHVlZWVagZO9///sfkydPZuXKlfz222/YbDYGDRrksMynn37Krl272L17NytX\nruSLL74oszxaayZPnkxycjL79+8nMTHRembo4MGDWb9+PRkZGVbZV65caT3vrGbNmnz66adkZGSw\nYMECHnvsMX744Ycy1wfGs9def/11UlJS2LZtG5s2beJf//qXwzKrV6/mu+++44cffmDt2rV8+OGH\nxfI5c+YM3bp1IzIykhMnTrBs2TIefvhh9u7dW24ZhBCVmwRp4ory9PTkm2++QSnFmDFjCAgIoFev\nXvzxxx+0bduWs2fPsmfPHmJjY7nzzjtxc3Ojfv361jSbzUa9evUuev39+/cnKCiIKlWqMHDgQG66\n6Sarz1tkZKRDkBYTE2OdiP38/Ojbty9ubm54eHgQFRXl0AyzLEOHDsXPzw8nJycef/xxzp0759BP\noWXLlvTr149q1aoxceJEcnJy2L59e7F83nvvPWbPnk3dunVxdnZmxowZrFq1SpoWCXGDOnXqFP7+\n/qU+jys6Oppp06ZRs2ZNAgICmD59OkuWLLHmV6tWjWnTplGtWjXuu+8+3N3drWNTtWrV2LdvHxkZ\nGfj4+NCiRYsyy9KuXTt69+5NlSpVcHV1LXPZnTt3kpyczJw5c6hRowYuLi4VHggjOjqa0aNH06JF\nC5ydnXnhhRfYtm0bx44ds5Z5+umn8fb2pl69etx1113ExcWVmWejRo3o1q0bzs7OBAQEMHHiROv4\nbrPZaNGiBWvWrAGMINHNzY2wsDAAevbsScOGDVFK0blzZ7p3716stURJWrZsSVhYGE5OToSEhPD3\nv/+92Dll0qRJ+Pr6Uq9ePSZMmOBwfir06aefEhISwqhRo3BycqJFixb07duXVatWlVsGIUTlJkGa\nuOKaNGnCwoULOX78OD///DPJyclMmDABFxcX2rRpw5YtW9iyZQsdO3YE4M4777SmXWp/tMWLF9O8\neXO8vb2t5o0pKSkAdOnShezsbHbs2EF8fDxxcXHWHeqzZ8/y97//HZvNhqenJ506dSItLY38/Pxy\n1/nqq6/SpEkTvLy88Pb2Jj093VonQHBwsPW+SpUq1K1b16H5TqH4+HgefPBBq+xNmjShatWq/PHH\nH5e0TYQQ1yY/Pz9SUlJKvVGTnJyMzWazPttsNodjS+HNo0Jubm5kZWUB8NFHH7F+/XpsNhudO3dm\n27ZtZZbF/jhWnsTERGw220U97Lnod3J3d8fPz4+kpCRrWmBgoPXe/juV5sSJEwwaNIg6derg6enJ\n0KFDHY7R9jfw7G/egTFoVFhYGL6+vnh7e7N+/XqHtKU5dOgQERERBAYG4unpyZQpU4qls9+mRX+7\nQvHx8ezYscM6L3h7exMdHc3vv/9ebhmEEJWbBGniqrrlllsYOXKk1RessF9abGysFaR17NjRmnYp\nQVp8fDxjxoxh3rx5nDp1irS0NG699Varv0KVKlUYMGAAy5YtIyYmhoiICDw8PAAj0Dp48CA7duwg\nIyPD6idXXl+H2NhYXnrpJVauXMnp06dJS0vDy8vLIV1iYqL1vqCggOPHj1tNiOwFBwezYcMG0tLS\nrFdOTg516tS56G0ixLUqLy+PnJwc8vPzyc/PJycn54arVW7Xrh0uLi5WLU9RQUFBxMfHW58TEhJK\nPLaUpHXr1qxdu5YTJ07Qu3dvBgwYABh9vkpSdHqNGjU4e/as9dk+aAgODiYhIaHE36u0/AsV/U5n\nzpzh1KlTl3QcnDx5MkopfvrpJzIyMli6dKnDMbp///5s3ryZ48ePs3r1aitIO3fuHH379uWJJ57g\njz/+IC0tjfvuu69CzxL7xz/+wS233MLhw4fJyMjg+eefL5bO/txQ2m8XHBxM586dHc4LWVlZvPPO\nOxe7OYS4Zl1v5wUJ0sQVdeDAAV599VVr0I3ExESWLVtmNR3p1KkTX331FYmJiYSGhgJGTdrmzZuJ\ni4srFqQVFBSQk5NjvQo7xZfkzJkzKKUICAgAjA7f9gOFgHHHdMWKFURHRzvcLc3MzMTV1RVvb29S\nU1N59tlnK/R9MzMzcXJyIiAggLy8PGbOnGn1bSj0/fff8/HHH5OXl8cbb7yBs7OztT3sjR07lqio\nKOsC5eTJk1d1BDchrqZZs2bh6urKiy++yNKlS3F1dXXob3Uj8PLyYubMmTzyyCOsWbOGs2fPkpub\ny4YNG3jqqacYPHgws2bN4uTJk6SkpDBz5swKPbbk/PnzREdHk56eTrVq1fD09KRq1aoA1KpVi1On\nTpGenl5mHs2bN2f9+vWkpqby+++/88Ybb1jz2rRpQ+3atXn66ac5c+YMOTk5bN261cr/+PHjxQbR\nKBQZGcmCBQuIi4vj3LlzTJkyhbZt2xISElLBrVZcZmamNVBJUlISc+bMcZgfEBBAeHg4o0aNon79\n+jRp0gQwttO5c+cICAjAycmJDRs28N///rfC6/T09MTd3Z0DBw6UGFTNmTOH06dPk5iYyJtvvsnA\ngQOLLRMREcGhQ4dYsmQJubm55ObmsmvXLvbv338RW0KIa9v1dl6QIE1cUR4eHuzYsYO2bdtSo0YN\nwsLCuPXWW3n11VcBaN++Penp6bRt29a6o+rn50dAQAA1a9bkpptucshv2bJluLq6Wq+GDRuWuu7Q\n0FAef/xx2rVrR61atdizZw8dOnRwWKawXMnJyfTo0cOaPmHCBLKzs/H39ycsLIx77723Qt/3nnvu\noUePHtx8883YbDZcXFyKNQt64IEHWLFiBT4+PixZsoSPP/6YatWqFctr/Pjx9OrVi+7du+Ph4UFY\nWBg7duyoUDmEuN7MmDEDrbXDq3CwhxvJxIkTee2115g1axYBAQEEBwczb948evfuzdSpU2nVqhW3\n3347t912Gy1atHAYJbEsS5YsISQkBE9PT959912WLl0KGK0fBg8eTIMGDfD29i6xCR7AsGHDaNas\nGSEhIXTv3t0hwKhatSrr1q3jyJEj1KtXj7p167JixQrAaHbetGlTAgMD8ff3L5bv3XffzXPPPUff\nvn2pXbs2R48eZfny5Re62RxMnz6dH374AS8vL3r27EmfPn2KLRMZGcnGjRsdbt55eHgwd+5cBgwY\ngI+PDzExMfTq1atC63zllVeIiYnBw8ODMWPGlBiAPfDAA7Rs2ZLmzZvTs2dPHnrooWLLeHh48N//\n/pfly5cTFBREYGAgkyZNKvOGpRDXq+vtvKAqUi1/I3B1dc3PycmRoFXc8FxcXBxGnxTiRib7gxAG\n2ReEMLi4uBRkZ2dX/avXI0GaSSmlZVuIi9G0aVPefvttwsPDmTFjBkeOHLHuOpdl5MiR1K1bt9Sq\neKUUhw8fplGjRpe7yGVSSlWoT4UQNwLZHwybN29m6NChDs+HvFzc3d356aefaNCgQZnLPf/88/zy\nyy+lPpOyMklISCA0NJT09HSqVq1KeHg4Q4cO5W9/+1u5aUNCQnj//ffp2rVrsXl/5e9QHtkXhDCY\n+0LZHWgvA6k5EqUKCQmhevXqxUacat68OUophyGPL0ZaWhqjR48mMDAQDw8Pbr75Zl566aVLyvNq\n2Lt3L+Hh4Ve7GELcUObNm0erVq1wdnZm5MiRV7s4lvDwcHx8fByam40cOZLq1atbD4B2d3enWbNm\nABw7dgylVLEh7lNSUqhevfol9bWqjMLDw4sFWVlZWeUGaABTpkyx0hZut8o6KEC9evXIysqy+vIJ\nIf56lfW8cLEkSBNlql+/vsOzWfbs2UN2dvZlyfuxxx4jKyuL/fv3k56ezieffFJmnzIhhCgUFBTE\n1BfNlrkAACAASURBVKlTGT169NUuiuXYsWPExsailOKTTz5xmPfUU09ZD4DOyspi9+7dDvPPnDnj\nMJBRTEwM9evXvyLlFkKI60FlPC9cCgnSRJmGDRvG4sWLrc+LFi1i+PDh1ufPPvuMO+64A09PT4KD\ng4t10Fy8eDE2mw0/Pz+ee+45QkJC2LhxIwC7du0iMjISHx8fqlSpwi233EK/fv2Aku+S2t+BPXLk\nCJ07d8bLywt/f/8SO10XNX78eIKDg/H09KRly5bWA0eTk5NxdXUlNTXVWvbHH3/E39+f3Nxcjh49\nSpcuXfDz88Pf358hQ4aQlpZmLWv/nYrq378/gYGBeHl50alTJ/bu3eswPyUlhW7duuHh4UHnzp0d\nhpa2d+7cOZ544gnq1atHrVq1GDt27GULloW4FvXp04fevXvj5+d3tYtiWbx4MWFhYYwcOZJFixZd\nUNphw4Y5pFm8eLHDsbYsiYmJ9OnTh4CAAPz8/Bg3bhxgjH47a9YsbDYbNWvWZPjw4daojIXH2EWL\nFlGvXj38/f2ZPXu2lWd2djYjR47Ex8eH0NBQdu3a5bBOpRRHjhyxPo8cOdJhUJK1a9fSvHlzPD09\nadiwIZ9//jlRUVHExsYybtw43N3drXIW5rV9+3YCAwMdnj+5evVqbr/9dsAYFKBwdMrCkX69vb1x\nd3fn66+/xtfXlz179lhpT5w4gaurKydPnix1250+fZqIiAgCAgLw8fEhIiLCakq4fPlyWrVq5bD8\n66+/bg0OUtb5r6yavvLOKWCcH0NDQ/Hx8WHUqFGl9gVLTk6mb9++BAQEUL9+febOnVvqdxXielcZ\nzwuXQoI0UaawsDAyMjLYv38/+fn5rFixwmEI5xo1arB48WLS0tL47LPPeOedd6xn9uzbt4+HH36Y\n6OhofvvtN9LT0x0eOBoWFkZUVBQLFizg8OHDF1SuZ555hu7du3P69GmOHz/OP//5z3LTtG7dmri4\nOFJTU4mMjKR///7k5OQQFBREu3bt+Oijj6xlY2Ji6NevH9WqVUNrzeTJk0lOTmb//v0kJiZWeLSg\nHj16cPjwYU6cOEGLFi0YMmSIw/zo6GieeeYZUlJSaN68ebH5hSZNmsShQ4eIi4vjyJEjJCUlMXPm\nzAqVQQhxZSxevJghQ4YwZMgQvvjiiwt60PzQoUNZvnw5+fn57N+/n8zMTNq2bVtuuvz8fCIiIrDZ\nbBw7doykpCQGDRoEwMKFC1m4cCFfffUVv/zyC1lZWVZgVOibb77h4MGDbNq0iZkzZ1pDtz/77LMc\nPXqUo0eP8sUXX1xQ0Llz506GDx/OnDlzSEtLY8uWLYSEhDB79mw6duzIvHnzyMrKYt68eQ7pwsLC\nqFGjBv/73/+saUUfHl2o8FmVhc8F69y5M4MGDXLoD7xs2TK6du1qPXalJAUFBYwaNYr4+HgSEhJw\ndXW1tlGvXr04ePCgw/nJvjxlnf/KUpFzSnR0NF988QVHjx7l0KFDJfZdLigo4P7776dZs2YkJSWx\nadMm3njjDb744otyyyCEqPwkSBPlKqxN+/LLL7nlllscHhoaHh7ObbfdRpUqVbj99tsZPHgwX3/9\nNQCrVq3i/vvv584776R69erMnDnT4UGlb731FkOGDGHevHmEhobSqFEjNmzYUKEyVatWjfj4eJKT\nk3FxceHOO+8sN83QoUPx8/PDycmJxx9/nHPnznHw4EHAGF65sFmn1prly5dbJ+JGjRrRrVs3nJ2d\nCQgIYOLEidZ3LM/o0aPx8PDA2dmZGTNmsHv3bofnC/Xs2ZNOnTrh7OzM7Nmz2bZtm8MDTAvLM3/+\nfF5//XV8fX3x8PBgypQplzzstBDi8vnmm2+Ij49nwIABtGzZkoYNGxITE2PNf+WVV/D29rZeI0aM\ncEhft25dGjduzMaNG4u1WCjLzp07SU5OZs6cOdSoUcPheBgdHc3EiRNp0KAB7u7uvPDCCyxfvtyh\ndmf69Om4urrSrFkzmjVrZjXDXLlyJVFRUfj6+hIcHMyjjz5a4W3xwQcfMHr0aLp160aVKlWoU6cO\nt9xyS4XSDh482DoWZ2Zmsn79egYPHlyhtCNGjCAmJoaCggLAeIzAsGHDykzj5+dH3759cXNzw8PD\ng6ioKOv47ubmxgMPPGCV5/Dhwxw4cMCqSSvr/FeWipxTxo0bR3BwML6+vkRFRTl0Oyi0a9cuTp48\nybRp06hevToNGjRgzJgxcm4Q4johQZoo17Bhw4iJiWHhwoXFLhx27NjBXXfdRUBAAF5eXrz77rvW\nQCPJyckOzwRzc3NzqIJ2dXVlypQpfP/995w6dYoBAwbQv39/h2aHpXn55ZfRWtOmTRuaNm3Khx9+\nWG6aV199lSZNmuDl5YW3tzfp6elWWfv168e2bdtITk5my5YtKKXo2LEjYDSZGTRoEHXq1MHT05Oh\nQ4cWG0ylJPn5+Tz99NM0bNgQT09PawAA+7T228fd3R1fX99izx06efIkZ8+epWXLltYF3r333ltm\nEx4hxJW1aNEiunfvbj3bKzIy0qH26YknniAtLc16lVQzNXz4cBYuXMiyZcsq9NBpMJo62mw2nJyc\nis1LTk7GZrNZn202G3l5eQ41fIGBgdZ7Nzc3srKyrLT2xyf7fCpSpovtXxwZGcnHH3/MuXPn+Pjj\nj2nRokWF1134nMuvv/6aAwcOcOTIkXKfW3b27Fn+/ve/Y7PZ8PT0pFOnTqSlpVlNLu1v4MXExNC7\nd2/c3NyAss9/ZanIOaXoti/peXSFNyrtg//nn3/+gmpwhRCVlwRpolw2m4369euzfv36Yg/5jIyM\npFevXiQmJpKens7YsWOtIXpr167tMExwdnY2p06dKnEdnp6eTJkyhTNnzvDrr79So0YNwDiBFvr9\n99+t94GBgcyfP5/k5GTee+89Hn74YYf+EUXFxsby0ksvsXLlSk6fPk1aWhpeXl5WWb29venevTsr\nV64kJiaGwYMHW7V+kydPRinFTz/9REZGBkuXLq3QMMQxMTGsXbuWjRs3kp6ebo2GaZ/WvtYsKyuL\n1NRUgoKCHPLx9/fH1dWVvXv3Whd46enp1sWUEOLqys7OZuXKlXz99dcEBgYSGBjI66+/zu7du4sN\nEFKWvn378tlnn9GgQYMKBybBwcEkJCSU2PcpKCjIoZ9rQkICTk5O1KpVq9x8a9eu7XB8SkhIcJjv\n5uZW6vE5ODiYo0ePlpivfWuKkoSGhmKz2diwYUOpTR3LymfEiBEsXbqUJUuW0K9fP1xcXMpc36uv\nvsrBgwfZsWMHGRkZVjPKwuN09+7dSUlJIS4ujmXLljmUp6zzX1kqck4puu2LnhfA2M7169d3CP4L\nax+FENc+CdJEhXzwwQf873//s4KnQpmZmfj6+uLi4sLOnTsdmvf069ePdevW8e2333L+/HmmT5/u\ncCJ67rnn2LVrF+fPnycnJ4c333wTb29vGjduTEBAAHXq1GHp0qXk5+fz4YcfOpz0//Of/1gBoI+P\nD0qpMoc6zszMxMnJiYCAAPLy8pg5cyYZGRkOy0RGRrJ48WI++ugjhxNxZmYm7u7ueHt7k5SUxJw5\ncyq0zTIzM3F2dsbPz4+zZ88yZcqUYsusX7+eb775hvPnz/PMM8/Qtm1bhzuoAFWqVGHMmDE89thj\nnDhxAoCkpCTpdyBuaHl5eeTk5JCfn09+fj45OTlXbTj2NWvWULVqVfbt20dcXBxxcXHs37+fjh07\nOgy8VJ7C/lgX8hywNm3aULt2bZ5++mnOnDlDTk4OW7duBYymg6+//jq//vorWVlZTJkyhYEDB5ZY\n61bUgAEDeOGFF6x+v2+99ZbD/ObNmxMTE0N+fj6ff/65Q3O9hx56iAULFrBp0yYKCgpISkriwIED\nANSqVYtffvmlzHVHRkYyd+5ctmzZQv/+/UtcJiAggCpVqhTLa9iwYaxevZqlS5dWqMloZmYmrq6u\neHt7k5qayrPPPusw38nJiX79+vHkk0+SmppKt27dHNKWdv4rb53lnVPefvttjh8/TmpqKs8//3yJ\ng2O1adMGT09PXnrpJbKzs8nPz+fnn38uNsiLEDeKynReuBwkSBMV0rBhw2KjXAH861//Ytq0aXh4\neDBz5kwGDBhgzWvatClvvfUWgwYNonbt2nh4eFCzZk2cnZ0B407oqFGj8Pf3JygoiC+//JLPPvsM\nd3d3AObPn8+cOXPw8/Nj7969tG/f3sp7165dtG3bFnd3d3r16sWbb75Z5nDV99xzDz169ODmm2/G\nZrPh4uJSLBjq1asXhw8fplatWtYzjMDos/HDDz/g5eVFz549i9Umlmb48OHYbDbq1KlDaGgoYWFh\nxZaJjIzk2WefxdfXl++//57o6OgS83rppZdo1KgRYWFheHp60rVrV6s/nRA3olmzZuHq6sqLL77I\n0qVLcXV1LfXB8H+1RYsWMWrUKOrVq2fVpAUGBjJu3Diio6PJy8vj5ZdfdnhOWmGzyKJatWp1QU0F\nq1atyrp16zhy5Aj16tWjbt26rFixAjD6xA4bNoxOnTpRv359XFxcigVbpZk+fbrViqJ79+7F+na9\n+eabrFu3Dm9vb6Kjo+ndu7c1r02bNixYsIDHHnsMLy8vh5Frx48fz6pVq/Dx8Sm1n9vgwYPZvHkz\nXbp0KXU7ubm5ERUVRYcOHfD29mb79u2A0bevRYsWDk3WyzJhwgSys7Px9/cnLCyMe++9t9gykZGR\nbNy4kf79+zsEuGWd/8pSkXNKZGQk3bt3p0GDBjRo0MBh5MxChb99XFwc9evXx9/fn7/97W8O/Z6F\nuJFUpvPC5aDk6fEGpZSWbfHXysrKwtvbm8OHD8vzfyoxpVSFmuwIcSOQ/eHaM3r0aIKCgq7pi7PK\nSPYFIQzmvlB22+3LsR7Z4Qyurq75OTk5UrMobnguLi6lPpNHiBuN7A9CGGRfEMLg4uJSkJ2dXXof\nm8tEgjST1KQJYZC7pUL8SfYHIQyyLwhhuFI1aVJzJK45ISEhbNy48S9fz8iRI0vsB1AR4eHhF9T5\nvyTu7u6ldrBfuHBhhZ4NJ8Tlsnz5cpo0aUKNGjVo2LAhsbGx7Nu3j1atWuHj44OPjw9du3Zl3759\nVpoZM2ZQrVo1h75Yhf/TsbGxDtPd3d1RSlkPlV++fDmNGzfGy8uLmjVrMmLECIfBfsLDw3FxcbHS\nNm7c+MpuECGEEOIvJEGaEJVUVlYWDRo0uNrFEIIvv/ySSZMmsWDBAjIzM9myZQsNGjQgKCiIVatW\nkZqaSkpKCr169WLQoEEOaQcOHEhWVpb1Kvyf7tixo8P0Tz/9FHd3d2vghg4dOrB161bS09P55Zdf\nyMvLK3bTZN68eVZ6GUhHCCHE9aT8cXiFuA7l5eVVaBhqIYQxGt20adOsEUrr1KljzfP29gaM50pV\nrVq1zOcVlmXRokX069fPesxH0dFXLyVvIYQQ4lojNWnimrRr1y5CQ0Px8fFh1KhRVmfm+fPn06hR\nI3x9fenVqxfJyclWGqUUb7/9NjfddBM33XQTAAcOHKBbt274+vrSuHFjVq5c6bCe06dP07NnTzw8\nPGjbtq3Ds9q+/fZbWrdujZeXF61bt+bbb78ttbwffvghTZo0wcfHh3vuucfhAbOlUUpZF6WnTp2i\nV69eeHp60qZNm1IfFCvE5Zafn893333HyZMnadSoEXXr1mXcuHFkZ2dby3h7e+Pi4sI///nPYs8D\nXLduHb6+vjRt2pR33nmnxHWcPXuWVatWMWLECIfp33zzDV5eXnh4ePDRRx8xYcIEh/mTJ0/G39+f\nDh06sHnz5svzhYUQQojKQGstL6MjrBbXBpvNpps2baoTEhL0qVOndPv27XVUVJTetGmT9vPz099/\n/73OycnR48aN0x07drTSAbpr16761KlT+uzZszorK0vXrVtXf/jhhzo3N1d///332s/PT//8889a\na61HjBihfXx89I4dO3Rubq6OjIzUAwcO1FprferUKe3t7a0XL16sc3NzdUxMjPb29tYpKSlaa607\nd+6s58+fr7XWevXq1bphw4Z63759Ojc3Vz/33HO6Xbt25X5PQB8+fFhrrfXAgQN1//79dVZWlt6z\nZ48OCgrSHTp0uKzb1X69QhRKSkrSgG7ZsqVOTk7WJ0+e1O3bt9dTpkxxWC4rK0u//fbb+tNPP7Wm\n7d27VyclJem8vDy9detWHRgYqGNiYoqtY/HixTokJEQXFBSUWIbjx4/r6dOn64MHD1rTtm/frjMy\nMnROTo5euHChdnd310eOHLlM3/pPsj8IYZB9QQiDuS/89bHJlVjJtfCSg8+1w2az6Xfeecf6/Nln\nn+kGDRro0aNH6yeffNKanpmZqZ2cnPSvv/6qtTZ2qk2bNlnzly9fru+8806HvP/v//5Pz5gxQ2tt\nBGkPPfSQw3oaN26stTYuKlu3bu2QNiwsTC9YsEBr7Rik3Xvvvfr999+3lsvPz9eurq762LFjZX7P\nwiAtLy9POzk56f3791vzJk+eLEGauCJSU1M1oBcuXGhNW7VqlW7evHmxZfPz87Wvr6/+448/Sszr\nhRde0H369Ck2/e6779bTpk0rsxzbtm3Td9xxR6nz77nnHj137twy87gYsj8IYZB9QQjDlQrSpLmj\nuCbZ91ex2WwkJyeTnJyMzWazpru7u+Pn50dSUlKJ6eLj49mxYwfe3t7WKzo6mt9//91aJjAw0Hrv\n5uZGVlYWQLF1FZbDfl326xk/fry1Dl9fX7TWJS5bkpMnT5KXl1fsOwtxJfj4+FC3bl2UKn+04YKC\nAs6ePVvq/3ZJQ3gnJiayefNmhg8fXmbeeXl5ZTbzleHBhRBCXE8kSBPXpMTEROt9QkICQUFBBAUF\nOfT1OnPmDKdOnXIY5MD+QjM4OJjOnTuTlpZmvbKyskrtN2Ov6LoKy2G/Lvv1vPfeew7ryc7Opn37\n9hX6rgEBATg5ORX7zkJcKaNGjeKtt97ixIkTnD59mjfeeIOIiAi+/PJLfvzxR/Lz88nIyGDixIn4\n+PjQpEkTANauXcvp06fRWrNz507mzp3LAw884JD3kiVLaN++PQ0bNnSYHh0dTUJCAlpr4uPjiYqK\n4u677wYgLS2NL774gpycHPLy8oiOjmbLli3cc889V2aDCCGEEH8xCdLENentt9/m+PHjpKam8vzz\nzzNw4EAiIyNZsGABcXFxnDt3jilTptC2bVtCQkJKzCMiIoJDhw6xZMkScnNzyc3NZdeuXezfv7/c\n9d93330cOnSImJgY8vLyWLFiBfv27SMiIqLYsmPHjuWFF15g7969AKSnp/Of//ynwt+1atWq9OnT\nhxkzZnD27Fn27dvHokWLKpxeiEv1zDPP0Lp1a26++WaaNGnCHXfcQVRUFGlpaQwePBgvLy8aNmzI\nkSNH+Pzzz3FxcQGMZ501atQIDw8Phg8fzqRJk4oNDrJ48eJi0wD27dtH+/btcXd3p0OHDjRu3Jj5\n8+cDkJuby9SpUwkICMDf35+33nqLNWvWyLPShBBCXD+uRJvKa+GFtLW+ZthsNv3888/rJk2aaC8v\nLz18+HB95swZrbXW77zzjm7QoIH28fHRPXv21ImJiVY67AbiKHTgwAF93333aX9/f+3r66vvuusu\n/eOPP2qtjT5pUVFR1rJfffWVrlOnjvU5NjZWt2jRQnt6euoWLVro2NhYa559nzStjT5st956q/bw\n8NB169bVo0aNKvd72pf3xIkTumfPntrDw0O3bt1aT506VfqkCXEFyP4ghEH2BSEMXKE+aUpLG34A\nXF1df8/Jyal1tcshxNXm4uJSkJOTI7XsQiD7gxCFZF8QwuDi4vJHdnZ2YPlLXhoJ0oQQQgghhBCi\nEnG62gUQ4kallOoIbChpntba/QoXRwghhBBCVBJSkyaEEEIIIYQQlYi0LRZCCCGEEEKISkSCNCGE\nEEIIIYSoRCRIE0IIIYQQQohKRII0IYQQQgghhKhEJEgTQgghhBBCiEpEgjQhhBBCCCGEqEQkSBNC\nCCGEEEKISkSCNCGEEEIIIYSoRCRIE0IIIYQQQohKRII0IYQQQgghhKhEJEgTQgghhBBCiEpEgjQh\nhBBCCCGEqEQkSBNCCCGEEEKISkSCNCGEEEIIIYSoRCRIE0IIIYQQQohKRII0IYQQQgghhKhEJEgT\nQgghhBBCiEpEgjQhhBBCCCGEqEQkSBNCCCGEEEKISkSCNCGEEEIIIYSoRCRIE0IIIYQQQohKRII0\nIYQQQgghhKhEJEgTQgghhBBCiEpEgjQhhBBCCCGEqEQkSBNCCCGEEEKISkSCNCGEEEIIIYSoRCRI\nE0IIIYQQQohKRII0IYQQQgghhKhEJEgTQgghhBBCiEpEgjQhhBBCCCGEqEQkSBNCCCGEEEKISkSC\nNCGEEEIIIYSoRCRIE0IIIYQQQohKRII0IYQQQgghhKhEJEgTQgghhBBCiEpEgjQhhBBCCCGEqEQk\nSBNCCCGEEEKISkSCNCGEEEIIIYSoRCRIE0IIIYQQQohKRII0IYQQQgghhKhEJEgTQgghhBBCiEpE\ngjRxQ1FKBSqlliuljiql9iml1iulbr4M+YYrpT69yLS9lVKhdp9nKqW6lpNmvVLK23w9fBHrrF1Y\nXqWUm1IqWim1Ryn1s1LqG6WUu92y7ymlOlQw3+pKqS1KKacLLVMF85ffj2v39xNCCCFExUiQJm4Y\nSikFrAY2a60baq1DgSlAratbMnoD1kW+1nqa1npjWQm01vdprdMAb+CCL/KBicB88/144A+t9W1a\n61uBh4Bcu2XbAtsrkqnW+jywCRh4EWUqk/x+Dq65308IIYQQFSdBmriR3AXkaq3fLZygtY7TWscq\nwxyzJmKPUmogWDUsm5VSq5RSB8waC2XOu9ec9g3QpzBPpdQMpdQTdp9/VkqFmO+HK6V+UkrtVkot\nUUq1B3oBc5RScUqphkqphUqpfkqpHkqplXb5hCul1pnvjyml/IEXgYZm2jlmng/YpYlWSvUqYVv0\nBT4339cGkuy2yUGt9TkzfRPgkNY639wOr5s1LfuVUq2VUh8rpQ4rpWbZ5b0GGFLhX6Xi5Pf707X4\n+wkhhBCigqRJi7iR3Ap8X8q8PkBzoBngD+xSSm0x590BNAWSga1AB6XUdxg1GV2AI8CK8laulGoK\nRAEdtNYpSilfrXWqUuoT4FOt9SpzucIkXwLvKaVqaK3PYNRuFF3P08CtWuvmZtrOwGPAWqWUF9Ae\nGFGkHPWB04UX8sCHwH+VUv0walEWaa0Pm/N68GcwAHBea91JKTUeWAu0BFKBo0qp17XWp4Cfgdbl\nbY+LIL8f1/TvJ4QQQogKuqFq0pRSWin1qt3nJ5RSM8pJE27eLb+c5Si8i150urtS6h1l9Lf5USn1\nvVJqzOVc9+Vg1jQkmXf/9ymlBl/GvCcopYbbfZ5o1nbsMWsvXlNKVTPnHTOn/6SU+lopZTOnX0y/\nmjuBZVrrfK31H8DX/HmhulNrfVxrXQDEASHALcCvWuvDWmsNLK3AOroAq7TWKQBa69SyFtZa52Fc\nYN9vfpeeGBfWZaX5GmiklKoJDAY+MvOxVxs4aZcmDmgAzAF8MQKcJubse3C8yP/E/LsH2Ku1/s0M\nFn4Bgs388oHzSimPssp6mcnvd23/fgCYNX0T7D5/oZR63+7zq0qpiWWkv6g+fiXks1kpddA8xsWZ\nAfCl5tlcKXWf3edeSqmnLzVfcX1TSuWb/4M/K6X+o5Ryu0z5dlRK7TXzbqKU+rkCadYrpbxLmO7Q\n+qDI9CS7/SiuML1Sqo15nj5onuPfL+m7KaXuKDwGKKVqKaU+Na8F9iml1hdZ9nOlVJ2KbDOlVIBS\n6vOi08v5/n/5Nisjn2L9ppXZasN8r5VSS+zmvamUSiuaprwyFF6fXsx1VNHrZaXUWPvruQqkjzK3\n70/mNm5b0bSXW1nHa/vtXiRNK6XUXPP9SKXUPPP9BW0HezdUkAacA/qoEgKkMoRj3M2uMKVU1QtZ\n3s77wGngJq31HcC9GBddldHr5t3/BzBqC6pdaobmwWA0EGN+Hgt0B8K01rdhXHSfAFztkt2ltb4d\n2AxMhTL71ezFqDkocfVlFO2c3ft8/qyB1qUsn4fjvuVit47S0pRmBTAAI0DYpbXOrECaJRjN1UYB\nC0qYn21XJgC01lla64+11g9jBCz3mSc2b611st2ihduiAMftUoBjzbwzkFOBsl4I+f0M1+rvVxHf\nYh5vlVJVMGpFm9rNb49RG1qaC+7jpwwlnQuHaK2bm69VFUxTluaAddLXWn+itX7xAvMQN55s83/w\nVuA8MLYiiSrwPzoEeMU8j2dXJE+7vrQX4nW7/ai51jpNKVUL+A8wSWvdGGiCcTOppBtDU4C3zPcz\ngS+11s3MPsnWTQ6llCvgq7VOogLbTGt9EvhN2Q2qVIm22cU4A9yqlHJVSvliXDsdu9jMLrJ/cjh2\n18ta63e11osrklAp1Q6IAFqY13RdgcQLWPfldsHHa631d1rrR0uYXuHtUNSNFqTlAf/GaE7kQCl1\nv1JqhzJqsDaad2xCMHbux8yovmPRCFoplWX+DVdKfaWUisG4S41Sao0yasP2KqX+r6yCKaUaAm2A\nqeYdf7TWJ7XWL5nz3ZVSm5RSPyij9ugBc3qI3V2on5XRh6WrUmqrMvqatDGXm6GUWqSU+q95p6SP\nUuplM6/P1Z+1U9OUUrvMvP6tlCrr4hezWdVZwMdMP8ZMv1sp9ZEyRp7zUEr9arcOT7MMRQO7LsAP\ndjUHUcA/Cg9wWuvzWusXtdYZJRRlG1DH7nNJ/Wr+Bzgru9pJZfTL6QxsAQYqpaoqpQKATsDOMr76\nAaC++buBUetR6BjQwsy/BVDfnL4JGKCU8jPnFQbgmZR8cgIj+GwBjKHkJnklpV0ITADQWu8tIc0h\njNokzHJ0UEoV/n7VMQbBiMfoA/ZVKeUqlfn9Tmqtc8td+MLI72e4Vn+/itjKnyf5phhNLzOVmwbG\nFAAAIABJREFUUj5KKWeMi7kfSzseUqSPH4BS6knzmPSTUupZc1qIMvrl/Qv4AbMWsSwlpVFGy4fv\nzGP8s3bLtlZKfWseB3cqo+nqTIz/0Til1EDleKfVZn6fn8y/9czpC5VSc828flGXoUZPXNNigUZg\ntTL52XxNMKeV9D/aXSm1zdxX/mPuO3/DuHk0TSkVbb8C+/9L8/OnSqlw873VCkgZtR4HlVIbgcYX\n+D0ewWiWvQ1AG1aZrSDsy+IB3K613m1Oqg0cL5yvtf7JbvFwjOMtgJtS6nml1DaMVhZhyqiVT1FG\nzV7hNlsDjK1M28zc599VSsUqpQ4ppSIquE0BNmC02OiHEZwusyvDYqVUplLqjPm9CtdfTSm10jz2\nrDC3cTNz3iTgWfM4tl0ZwXVhLeRH5nF1l3kOCqH49bJVU6eUaqSMa+vd5voLz72FagMphc34tdYp\nhTcYi2zDVkqpzeb7zurPGtofzf8XlFJPqT9bX71oTmuojGvd781te0tp21sZ59FSj9emrkV/I1XK\nKNGF28Esww92029SSpXWhQO48YI0gLeBIco4adr7BqPG5g5gOfCU1voY8C5/3gmKLSfvNkCUeYcH\nYLTWuiXQCnhUmRd3pWgK7C4M0EqQAzyotW6BcfH1qlJWANUIeBO4HaMZVyTGgekJjLtQhRpi7MAP\nYNxt/8qsoco2pwPM01q3Nu9AuWLc2SiVMi5iD2utT5iTPjbTNwP2Aw+ZtQeb7dYxCKMZV9GLwA6Y\nfY7Mnc1da/1rWeu3cy/GAbdQsX41ZrO2B4FuymhSuheYgdFXaTXwE7AbIxh4Smv9e2kr01rnAP8H\nfKaMgSfi7WZ/BPgqpeKAf2BcVBdecM8GvlZK7QZeM5dfDjxpHmQcDlxm07NPMfoWFdv5tdGHaKt5\n0pljTvsDY9uXVAuDNvpHHVVKNTInNTTLtAf4EfjO/A5F+zNV1F3A+nKXukDy+1lprsnfryLMk3Ke\nMoKU9hg3X3YA7TCOoz+Zd3hLOx4+DRw1j9dPKqW6AzdhHJubAy2VUp3M1TUGFmut79Ba2//+haLt\nLgD8SkkTpbVuhXHs7ayUut08wa8AxpvHwa4Yd7mnASvMshUN2OeZ+d4ORANz7ebVxjieR2AEoeIG\npIyWJj2APUqplhg17W2BMGCMUuoOc1HrfxTj/24q0NXcV74DJmqt38do+vyk1vqCBwky1z8Io79v\nH8ruw/qY3X5UeNOorP7F9lphnMsLvQ18oIwb4lFKqSC7eUWPd4lAR4yb8+2BWRgtcaphbjOMa5/W\nVL5tFgJ0xrhmelcpVdhyoqPdtozDGLTK3nJzHR0xbv7tsJt3DONm+j8wArjnzelPY9wgL8AIzqrb\npXEFAszj2BaMbQbG9ebrWuvWGINYvV+B6+Vo4G0zr/bAb0Xm/xcjQD6klPqXMm6+lucJ4BGzZrMj\nkK2U6oEx4nJbc10vm8v+G/ineU3+BPAvu3xCsNveGLFRWcfrYmnsfqNSaa2PAulKqebmpFEYN2VL\ndcMNHKK1zlBKLQYexbG6ui6wQilVG+OftKLBgb2dRYKKR5VSD5rvgzEuFk5VJCOlVBTQH6iptQ7C\naGr1vHmBUYBRa1Q49PivWuvC2ru9wCattTYv2kLsst2gtc41p1flzwOa/XJ3KaWeAtwwmlruBdaV\nUMTHlFGj0QAjQCp0qzJGivMG3IEvzOnvA09hBFKj+HNnt1cb4+IUijQtU0rdA7xk5huptf7WnPWV\nMu7unMBs7gjGxbFS6rxSykPbNTEzLwIHlLBugCfNl0VrvZk/786htR5n9/5zjKCYImmyMZoaFKO1\nXgQsKjJtK3ZDuAMji8wfB4wrMi3E7n2k/TxlNHO7CfMuWinmmeuZalbDF6uKV0bbcqvWWWsdbvd+\nM47bJfzPlEQCk8tY90WT389yTf5+FVRYm9YeIxCuY75Px2gOCWUfD+11N18/mp/dMbZtAhCvtS7r\n0QRDtNbfFX4wbxwVTTNAGa0knDCOX6EYx63ftNa7wDjnmOnL+s7t+HOE0SX8eWEBsMa8ebfPPNaJ\nG4ureUEORk3aBxgX2qvNGzYopT7GuEj9BMf/0TCM/8mt5v9fdYwbH5eqo7n+s+b6Pylj2de11q9c\n5HqK9r/9QilVeM3RA6NW/VZtNF3sgHHxDcbxYRzwd4xruXiMFg2rMI6bTsDHGNumFpVvm6009/nD\nSqlf+PM8Fau1tm6cK6UW2ifSWv+kjBotF4ygyt4XGE1MbzLz88a49kvECF6+MvO0bwZ/Hsgyj33f\nA93M6V2BULtjmqcqow+zOa+O1nq1Wc5iTem11llmINsR48bbCqXU01rrhUWXtbMVeE0ZNZsfa62P\nK+MZpQsKt7M2BvdyxziH/MeuzM52+ZS2vctyMWnAuBYepYy+1QMxbiCW6kasSQN4A+NZQjXspr2F\nUYt0G8aOXVpUbPVXMe/c2t91OFP4RhlV3V2BdmY0/2MZeQLsA5opsz201nq2eXfA05w/BAgAWprT\n/7DLr2jfEvt+J/aBeGE1cgHGUObafjnzTsC/gH7mdphfRplf10Zb8oHAYru7CAuBcWb6ZwvTmxey\nIebdkapa65I63GbbLZ8BnFHGSHZorb8wv/fPOG7zuwAbRjA5s0h+V6tfzVVjHqAOAG9prdNLW848\nWB4rKy+tdQt9gU3ezFqENVrrgxeSThjk9wP+7Jd2G8b+vh0jiLHvj1bW8dCeAl7Qf/aHaaS1/sCc\nd6aE5ctjf4yvj3FReLdZA/aZWYaL6btYlH16++N7mZGeuC5l2/3//lMbNcll/R/Y/18rjD5chelD\ntdYPlbO+0vrkFnUp/+Nl9S+2V1L/21StdYzWehiwC+hkBm6J5rYpLFtn89iw1MyncJvZXxf9P3v3\nHR5VlT5w/HsmPdSEGgKEGjCAIpFupYmKdBDEti4gq65ldZd11R+ua2FV7KICi4iiiIICCjaqCgEJ\n0msoEUKJQIBQQsqc3x/nJkzCpCdzZ5L38zzzZObOnXvfuVNy3znnvCcAc47gbccs73rFOdYLgGhM\n8SxXj2K6v18JnKbg89FsGVw8j3Idz+3AnNtmH6NIXfB46yJ9b2lT+Gu51noCJskeYt3lenyDXdaf\nCIzGtPjFKdOF0d33rwM4qXOPjbzM5f6SHO+SvkbZvVz6AfHa9KbJV6VM0rSpyjYHk6hlq8HFuYZc\nS17nHTOyn4tfLgMwH3J3amDKZJ+z3jhdCokpAdOs/pyyCo9YiU/2m7sGkGy1hGUnJmUt+81/zPrl\nodDxD1rreZi4s49ZNcxg3AAuHRM2E9M64LYbF6YVrYXL7ReBd9XFalAKN18sVsvHI8BdyhonpOwd\nV2MbrfWPWuvGWuvXi7DutMLWKcH+03UJB8gKef0sv2D+gZ2w/mmfwPzq25WLv2jn932Y9/v6O+Be\n6/sMZSq/1S2jOKtjTu5OWS1cN1nLdwANlFIdrX1Ws7qqFTR2cRWmmxKY782fyyhGUTGtBAYqM+a7\nCqYbuLvhGHGYKUeyx7GFKqWiC9n2fqC9UsqhlGqE+1/6VwKDlClSUQ24tZjxvw3crVyq9yml7lBK\n1c+zXq5zAqVUD6unQXbrTHNMq3hRunavxHSDU5ieQoMw53y78qznDcdsmLWt5pjeSsX50Wy6ta+8\nBexaY57vbbi0TmJaGocDKKViyP0jOLg/j/oel94hLt333H7HWT+6H1RKDbTWD1J5Km4qpVoppVq6\nLGrPxWEI+7l43j3E5THNtdabtandsM56jt9jvvOz3yfh1v73KaWGWcuUUip73B24P94FfV/n95hC\nWa2I3wHvkv+5cI5KmaRZJmEqh2V7BtMU+hNwzGX5QswHa4NS6hpM69J1Sqm1mP7g+f0a+y2mdWoT\n8B/MB78wo4FaQIIygwl/xAzcBNOf9ypl5ncahTkRKFPaFOiYimkC/wrzK1VRPAv8zWoFfBrTD/oH\nNzHOwvSJzq8b12JMwYds72KOwRrrOP6CaZH8Le8DtdaHre0+YC2ybVyNEKJUNmO+m+PyLDulrekP\nyOf7UOcZ46e1/h5TLXa1Mt28v6Dgf7xFpk0xg98wrQLTsVr5rF/zbwPeUmbs4g+YH5eWYboIbVDW\nZOsuHsJ0gdkE3Ak8XBYxiopJa70e02tlLeb/7TSttbv/i39guvd9ar234ii8W9YvmBP3zcArmGIa\n7vb/GWZKk7m4TxCzuY5J26CUaqLNuNsRwCvKFNLYjunmlqsomNZ6B1DDpStdLLDOei6rref9K6b7\nY4FJmssxi8CcJE8DGmDGMLuu5w3HbCemJWwxMM5d98D8aK0PYnoxXZ/nrtWYVsV3Md9JrsvrWM91\nPKaLY3armB/uz6Mewnz/blJKbeNi9cy858uu7sQMAdqE+VEqb0JeFfhQmakVNmG6nD5j3fdv4A3r\n/DzL5TGPWN/1GzGtpYu1GcawAPM+2cDFLrCjgD9b627FNLJkc3e8C/q+zu8xRTUL0/L2fWErqos9\n3oQoX8pUJhtgdVPIb50vMUUfdue3ThH3NQ94QrrdCSGEEL5JKfUokJpfzwFlqr7+ok0Bn+JueyXm\nnCSllGGWGWXGmX2t80z7UYLt/Az002bKg/3AVS4/crmu5wcEaK3TrFahJUC01jq9MpxHldXxLuY+\nHwdqaK2fLmzdSlc4RNhDKfUWpkvCzYWs+k/ML10lTtK8ZFyNEEIIIUrnXUwRNbe0KdlekgStDvCq\nNyVoZewxoDFQ2BxtoZgCbAGYrqB/sRI0OY8qB1ZDRHNMRc3C15eWNFGZKDPA+EnMrxgy51ApWeMh\nJmO6SCzXWs8q5CFluW95LYUQQghRIVXmMWnCxyilpiulkpVSW/Is72v1a09QSv2zoG1orfcWoVJT\npVbM4zwY+EJrPYZL52wpq3245auvpVKqmVLqf0qpMuteUZptels8QgghhJAkzTbKzKC+2RqUuM5a\nFq6U+kEptdv6G2Z3nK7cnVjnF7NVPedN62R7kzKTXpfWDHLPyZbdn/odTFfKGGCkUipGKdVOKfV1\nnktZVXWr6GZQxOOMmV/wgLWa64DeMttHaV5LpVQjZSY+3a6U2qqUKnFBBpf3/1al1Fql1Ebr+r+L\nm1xiJtLuqZT63V2yau2vwG3m+TyewFQ87GM910dKkuzmlzwXJZ78tlmYom5XKTVUKaWVUsXu2lTW\nivDa/E1ZA+CVUkuUUuVRjbfIihBvkFLqM+v+NcrMtSR8SEGfXV9Tlt/bJdz/Jednee4vj/ObksTZ\nSuUuynJaKfVInnX+oZTKUkpdUEodUkr9X5778/3sK6WesJbvVGau2uzlbr9PlFJNrW3straZt1Jk\nUZ9Xib+v3MVc0PtJKfWMUirJ5RgWNiTHs7TWcrHhgikpWjvPspeAf1rX/wn81+4488R3LWZCyC2F\nxYwZe7YY08e5C7CmjGJokmf/XYHvXG4/gRnoWth2vrD7eHrzpajHGVOxqZ+1bLa3vZaY8Y0drOvV\nMOWWY/KsUxeolmdZCzfbynn/A1WtZQGY6moHMWV4A4GNwNWY6q9fu1yWYianB/gbpnT0KjefqbqY\nhGuPyza3YxLXdi7bW4UptbwdM8H2aEz1wmBMpbEix5N9HN19xq37/PLEs9FNPNmXukV5bQrarpv1\nqlnPNQ4zAN7Oz0ahMWOqy4Za1/8CfObl8d4PvGddH2FnvHIp8evs9rPri5eifG+X8/73k+f8LM/9\n5XJ+U8qY/YAjQFSeZUnWd32xPvvW9/tGzDxpTa3vEL+Cvk8wU1uNsK6/hxnfVpLnUaLvqwJizvf9\nhKkg+bjdr19+F2lJ8y4DMCdbWH8H2hjLJbTWKzG/2LvKL+YBwExtxAE1lVIR5RBWJBdbcsCcLEfm\nt7JSqpZS6j3gSqXUE+UQT0WV33GeBwxRSr2LKb9bHvtwqyivpdb6sDalj9Fmss3tbrZ5HTBfWROy\nK6XGAG+62VbO+19rfcZaHICZw+ugNq1H6cBszIn5i5iJ4fsB84E0rXWyUqohcAsmkTrBpZ+p6zAV\ntvZq0+p2N+ZkYIA2c8L0sy7dgLswpXyvBbInab4S2FXUePJ7jnl0AhLybDNvPNmXZDePz4/b7bpZ\n7z+YH4S8YXL6QmPWWi/TWp+zbsZhWpztUpRj7Po9/gWmlVcmzvYhBXx2fU4Rv7ft5Knzm+LoCezR\nWie6LOuESdLOleCzPwDzw+sFrfU+IMHantvvE+sxPaxtQMnPYUvzfeU2Zh94P+VLkjT7aOB7pVS8\nUmqstayeNvN9Yf31he55+cVcrBPuUnB3IpFvNRyt9XGt9TitdXOt9YvlEE9F5fY4a63Paq3/pLX+\niy590ZByfS2tLhFXYlq+XLfzOWaOndlKqVHAvViTexawLT9l5mBJxnzhu3YxOgikFLDNydb9LTBV\nnvI+r8+tbbZ0eewr5P/5CbS2twMzQepHwOGixlPEHy7K68eQQrerlLoSaKS1/rqA7XhScb/b/oz5\n1d0uRYk3Zx2tdSZwCjNnpxC2yu97u5y5Oz9z5anzm+IYwaVz0EZiJq7uqsz8YCMwvR/yruPus5/f\nc8xveS3gpLUN1+XFVZrvq6L8P2nCpe+nB61uq9OVlw0zkiTNPt211h0w428eUEpdW9gDfEyxTrhL\n4SDQyOV2Q+BQOeynsvPEcS63fSilqmImEH1Ea3067/1a6+xWmneB/i4tZW5prbO01u2tGFtgJmnP\ns8ql21RK9cO0ug3FTK65J59dLMCM8XsXU5DlAgV/fi4H7tJaB2Em2byiKPFYdxQl2S2vBLrA7Sql\nHMBrmHLS3qLIx0IpdQemPPjL5RpRwYoSr6e+r4UossK+t8tRYednXvV5scZ+9Qc+z3sXcAzTBfIK\nzCTWecdc5fdcymp5cZXm+6qw/yfu3k/vYn4sbY/5cXNScQMuT5Kk2URrfcj6mwx8iWniPZrdZG79\nLU63IbvkF7OnkqdfMS0OTa0vqhGYE1xRtjxxnMtlH8rM/zIXmKW1npfPOtcAbTGfxQlF3bbW+iSw\n2npstobAoXy22R3or8zkorMx3UNec7PpWphW6ezHFvT5ycQkftm/DC4kd/e6guIpqvL6PBe23WqY\nmJdbx6wLsEDZWzykSMdCKdULM0VEf23mcrJLUeLNWUcp5Y8ZE1lo1zml1CU/Ziilximl7rKu36OU\nauBy336lVO2iBm49/u2irl8cSqn6SqnZSqk9yhR5WaSUii6jbQ9UprBSmXBzHKeV5fa9UVG+t8tL\nPudnrrztx+GbgPVa66N5lh8E6rv86Hgc0Hk+g/l99vN7jvktP4bp9umfZ3lxleb7Kt/H5vd+0lof\ntX50dQJTufS1tpf2goFxle0CVMEqVGBdX4WpdPcyuYtwvGR3rG5ib0LuIgduY8aMuXEdWLu2DPb9\nKeaXjgzMh/HP1vKbMQNB9wBP2n2MfP3iiePsqdfSev/NBF4vYJ0rMV0Fm2N+uPoEeC6fdZtguiLW\ntG6HAD9hBmw35eJA5yGFbRO4HlNoI+9nKjue3zGDp2cDR4E2+cSzxYqhlbXsWcwEpsWKJ+828yzz\nB/bm2eYl8ZTg9SnWdoHl2F84pNCYrddwD9DSzliLEe8D5B6IP6eI2z5TyP25Xi8KKcjg5vH3AG+X\nwzFRmB9Xxrksaw9cU0bbn4EZ/+n29SjB9or0vnf32fXFC0X43i7Hfbs9P8uzTpmf35Qy5tnAn9ws\n9wcSXT77uzD/d5XLOm4/+0Abchfh2IspwpHv9wmmJc+1cMj9JXguJf6+KiDmfN9PQITL9UcpZgG0\ncn9t7Q6gMl4wJ14brctWrJNRzK/nS4Dd1t9wu2PNE/clJ9b5xWx9KN7BnKhsLso/GLnIpawvmKqG\nGtgEbLAuN+dZpzvQzuV2ADDGzbZc3//pmL7vW4D/I09yWZRtYpK0JDefqe6YcQOu2/yykHiOYk6A\nNwFfYcabFSseN9vMSZ6t+8rlxxB328Ukmv3drLvcG75LCosZ+NF6TbLfcwu8PN5gzAlWArAWaFbE\n7V6SpGFVSwOGAmcw3W83YH7Q2A/8G1iP+b/Q2npMuPW+3YQptHK5tfwerCQNiML8j9lk/W1sLW9u\nPeZX6zmdsZZ/hClukx3XLJfn2wNY6SZ2hfnhcYsV320un9XlmCIFO6xtKeu+icA2K65XgG6YX/X3\nWc+7ufXYF4AVmK67M3BJ4lyPI/APa98brW27O445nwNgpLX+SWu97M9uGvC8tZ04zPhxWz83xXi/\nFvq9XY77zu/8bBxWUo8Xnd8AoZgWshouy1xjnYzpLn8B88NfN4r42cf879hjvfduclnu9n+BdezW\nWtv6HAgq4XMq8feVu5gLej9hvic2W/ctwCVp84aL7QHIRS5ykYtc5CIX37tQQJJmXc9JJqzb+4G/\nWtfvB6ZZ198CJljXewAbrOv3cDFJWwjcbV2/F/jKuv41MNK6Po6LSdp1LuvUwCRN/tbth4DX3MQ+\nBDNuxw+oZ53URmCStFOY7lMOTCvc1ZjkcicXE7bsFvYZ5E7ClgOTXW7nvT875pswLTfZ0zeE53Mc\nl2PGOjawYqyDaYFYCgy01tHArdb1l4Cn7H6/yEUucineRcakCSGEEMJTsseDxGO654FJeD4C0Fov\nBWoppWrkeVxXTDddrHWvdlmeXTAh+3601iuAFspMfD8SmKsvVp7Lz9XAp9qMUTmKafnqaN23Vmt9\nUJuxKxus2E9jWqymKaUGA+fcbDPbZ4XsG6AX8IG2pm/QWhc2LrAjsFxr/Yf13GZhpuMA09qfXRHV\n9VgLIXyEJGlCCCGEKA9NgDvyLMsuopKFaf2BklWGK+x+MMncKOBPwAcuy7cCsW7WL2huONfiL1mY\nVrlMTKGBuZg5ob4t4PFnXa5nYp1/WfM7BbrsvyjPqyjxZmits7fleqyFED5CkjQhhBBClIcLmEH8\nhVmJSaZQSl0PHNOXllxfhSkSgLXuz9b1OEw3RVzuzzYDeARAa73VZflSIMiauB5rvx0x8wneZs2D\nWAfTKrU2v6Ctkt41tNaLrP20t+5KxVQmzc9+LiaJAzBjRAG+B+5VSoVa2w8vZHtrgOuUUrWVUn6Y\nFsMVBexXCOFD5JcVIYQQQgA5k71+i0mCumAKKHyAKfhRF5Mg3YwpUhGqlDqIGb91DFN04xqgnVKq\nL2ZKliFKqa6Ybon5eQb4QCm1CdNl8G436zwETFdK/R0zQe+frOWPAB8rpR4DvsGMHQNMeW2l1HZM\nURJclmul1CDgdaXUPzFdFvdb26pqPWcN/ENrfUQp1TqfuKsB85VSwZhWrUet5bOBqUqphzCFP/Ka\naj1uLaYIylkrrm+VUu2BdUqpdGAR8C9MsvmeUuo8LsdRa33Ymix+mbX/RVrr+fnEKoTwMepia3jF\nYv2DeAMzAHia1nqizSEVSCk1Vms9xe44SsNbnoO3xFERefrYymtZefnia+9rMbuL10rSEjDTCGzF\nVE3ciKk82h+THG3AFLt4xXrMFqAfptrvDKAz5kfg9ZhS2a+U43MIBc5bidcITBGRAS73bQY6aK1P\nFbSdisLX3oOF8abn402xFEVp4/W15wu+GXNBKmR3R6vZ/x1MpaQYYKQPTPw41u4AyoAtz0Epdasd\ncbjZb7k9vrB1C7o/v/vcLc+7zJPHNp84vepzUdrXvKy3WdzHFmX90rzXyphXvfZF5Gsx5xfvPq31\nZqtIxlZgiTW+aTMFF6C4BjNdxDmru2JZT3jvTiywwWqFux9T4j57MvEdwFuVJUGz+Np7sDDe9Hy8\nKZaiKG28vvZ8wTdjzleFTNIwA3kTtNZ7tdbpmK4HA2yOSZQfT500lvV+i/P4wtYt6P787nO3PO8y\nTx5bu17H4iiPGEuzzeI+tijrl+a9JioG1yIZTpfbTkwLWU7hC0uwy3XX7jldMaXwy43W+iet9RVa\n68u11tdqrROs5T9qrRtrrV8vz/0LIUR5KdPujkqpb7XWfctsgyWPYyhmhvjR1u07gc5a6wfzrDeW\ni1l3bFBQUcY3lw+tNabIk+/y9HPIysoiKysLAKUULVq0ACAjI4OAgICCHlpm+/fz8/PI4wtbt6D7\n87vP3fK8y/LeLqtje/LkSU6dMj9uOxwOGjVq5DYeT72WRVXa17yst+n62CNnnQDUr5L/b29F2VdR\n3mupqamXvH5lzdte+6LwtZgTEhJwOp12h+ETatWqRZMmTfK9f+fOnQC0atWq1PsqaFt//PEHx44d\nA8z/3LyfPV97DxampM/H3f8Yu2KxS1Hjze9YZT/+Qhacy9CEBiiCyvbfX5nz1Gu0a9euY1rrOuW9\nn7IuHFK7jLdXUkUq52v1W50CUKVKFX327NlLHuQpy5cv5/rrr7dt/2XBzudw1VVXsW7dOtvjqOjK\n49i6vnae2F9Fddv7qwH47L6C6jOUvYJev9Lwxdfe12JWSrF58+Zcy+Lj4xkzZgy33normzZt4vz5\n8/Tr1481a9aQnJyMw+Hgpptu4vvvvyc4OJi2bduyYMECpk6dSmxsLGPGjGHdunVUqVKFqlWr0rx5\nc9555x2bnmHZueeeewp8n2e/7suXLy/1voq6LXefPV97DxamLJ5PWX1H+dqxLUm8ec+lqjW9gtve\nX02oUxPs72DWmC7ERoWVQ7Rlw1OvkVIqsdx3QsXt7ngQcP3ZpCFwyKZYhBBCCJ9Qv359nE4no0aN\nYu7cuVSvXp2jR48yc+ZMxo8fT8uWLfH392fo0KF88cUXPPPMM0RFRVG/fn22bt3KsWPHWLVqFd9+\n+y0Oh4OOHTsWvlMhhFeK23scp9XjLj3LSdze4zZHVLlU1BL8vwItlVJNgSTM3Cm32xuSEEII4T2U\nUrRr187tfUOGDMm5vn37dr766mIV+2XLlgEwadKknGV9+14c6dCpU6ec65MmTcq1nq+KjXU397UQ\nFVuXZrUI9HOQlulEKUWXZrXsDqlSqZBJmtY6Uyn1IPAdpgT/9DwTWVYMb74J06dDu3ZEwuCSAAAg\nAElEQVTm0rat+duwIfj4+DYhhBDlS2t9SXfHpKQkHnzwQb788ksAnnzySa677jr69OmTc1/fvn0J\nCAjg3nvvBeDmm29m6tSpLF26lNOnT/PAAw8A8NJLL1G3bl3uuecejz6v8lARnoMQxRUbFcasMV24\n/+N4LmTJ+FVPq6jdHdFaL9JaR2utm2utn7c7nnJRrx5ERMDy5TB+PNxyCzRuDGFhcPXV8Je/wOTJ\n8NNPkJJid7RCCCEqgAYNGrB9+3YAtm3bRlJSEmBam5YsWUJaWhpnz55l/vz5/Prrr3aGKoQoA8fP\npnPyXAa3T40jPlHOJz2lQrakVRq33WYuYJKwLVvMZfNm83f2bHjvvYvrR0bmbnFr1w4uuwyCg91v\nXwghhMijd+/eLFy4kKFDh9K2bVuioqIAiImJoW/fvgwbNoyIiAgiIiJsjlQIUVpxe4+T6TTj0jKt\ncWneXDykIpEkraIIC4NrrjGXbFpDUtLFxC07eVu2DC5Y0944HNCyZe7k7eqroW5de56HEEIIW2Vm\nZjJhwgQ2bdpEdHQ01apV48477+TEiRNMnDiR6dOn061bt5wugIMGDbpkG06nk2bNmhETE+Ph6IUQ\nZalG8MVUIcDfIePSPEiStIpMKTM+rWFDcBnUTWYmJCTkTt42boS5c01i53DA9dfD0KEweLDpVimE\nEKJSOHDgAJMmTWLChAmMGDGCRYsWMXPmTJYtW8bUqVNp3bq128dt3bqVxYsXM2fOHLKyshg+fLgk\naUL4sPjEFJ79ehsAfkrxf/3aSCuaB0mSVhn5+0Pr1uYydOjF5efOmYTt66/h88/h/vvhr3+FO+6A\nl16S1jUhhKhApLpj0Ul1R1EZxe09TkaW6eqo0aScS7c5ospFkjRxUWgodO5sLs8+a1rapk0zVSRP\nnIAFC+yOUAghRBmR6o5FVxGegxDF1aVZLYL8pQS/XSpsdUdRSkpBnTpw/ry53by5vfEIIYTwCkWt\n7rhixQo7wxRClFJ2Cf7mdaoQFhpAh8Y17Q6pUpEkTVzqyBF47DFo1gz+9z94/HF45RW7oxJCCOEF\nevfuzalTpxg6dChz5sxxW93x0UcfJSQkRErwC+HjYqPCuO/a5hw7k86EBVulBL8HSXdHcdGRI/Dy\ny/Duu6b64x13wFNPmeqPQgghKrzIyMicro4Azz//vNv7pkyZ4vbxY8eOZezYsQBMnjyZ0NDQcoxW\nCOEJdaoFAvDR6kTmrDvArNFdpICIB0iSVtlpDb/9Bh98YFrNLlyAO++EJ5+U5EwIISqZpKQkxo0b\nR4cOHXJK8A8cOJDJkyfnlOD/6aefCA0NzVWC/+233yYyMpIpU6awcOFC6tWrR3h4uFR3FKIC2HY4\nFQANZGTKXGmeIklaZXXoEMyaBR9+CFu3QmAgjBwpyZkQQlQSBVV33L9/PwAJCQksWrQoZ/ntt9+e\ncz2/6o6uj1+8eLFUdxTCx3VpVosAP0VGlsbhkAIiniJJWmXjdMIDD8CUKeZ6166me+Pw4RAebnd0\nQgghPCS/6o5jx47lm2++AeBf//oX3bp1o1+/fhw4cIBHH32UHj16uG1JW7p0KadOneLBBx8EpLqj\nEBVFbFQYn4zpwugP11EzJIC4vcdzlovyI4VDKpvPP4f33oP77oNdu2DVKhg3ThI0IYQQAAQGBuZc\nV0rl3HY4HGRlZeHn54fT6cxZ58KFC7nWF0JUPB2bhDO4QySJJ87xync7uX1qnBQRKWeSpFUm6elm\nUuqmTeHtt6VboxBCiGKTEvxCVE41QgIAMzbtQqaTf3yxieU7k3E6tb2BVVDS3bEyefJJWL/etKY5\nJD8XQghRfL1792bhwoUMHTqUtm3bui3BHxERQYcOHWyOVAhRlq5pWYf3VuwhPdOJQymOnUnjng9+\nJapWKLd3asywqxoRXiWw8A2JIpEkrbKYNMnMdfaXv8DQoXZHI4QQwguVZQl+IUTFEhsVxqzRXYjb\ne5wuzWrRLrIG3249wsdxiby4eAeTfthFv3YRdGwazomz6XRpVkvGrZWCJGmVxYsvwnXXweuv2x2J\nEEIIIYTwQbFRYbkSr/5XNKD/FQ3YeSSVWWsS+XzdQeb9loRSEOTvkDnVSkH6vFUGTiecPg316plS\n+0IIIUQ5mzx5MjNmzLA7DCGEB7SqX41nB7Rl7LXNADMNb/acaqJkpCWtMnA4oFEjU81RiDKSlgZ/\n/GHeWiJ/n6z5nfkbksp9P9sOnyYmonq570dUHAXNk1aWZJ40ISqPa6Pr8PbSBLK0JsDfIXOqlYIk\naZVFu3YQF2d3FKICeeQR+PJLWLgQOnWyOxrvNX9DkkcSqJiI6gxoH1mu+xAVS37zpI0bN44OHTqw\nadMmoqOjGThwIJMnT+bEiRNMnDiRn376ye08aZGRkUyZMoWFCxdSr149wsPDiYmJqRBzjFWE5yCE\nJ8RGhfGPvq14cfEO/n5jK+nqWAqSpFUWDodUdBRl6uGH4fvvzVDHjz+GIUPsjsh7xURU57P7utod\nhhBFcuDAASZNmsSECRMYMWIEixYtYubMmSxbtoypU6fSunVrt4/bunUrixcvZs6cOWRlZTF8+HBi\nYmI8HL2o6H5OOMbGAyelKEUxxe8/wcrdf3BtdN1yP253d2vCqz/sYsGGQ7RvFCavUwnJWXtlER4O\nhw+Dy6SjQpTGZZeZxtn27WH4cJg/3+6IhBBlITIykujoaBwOBy1atKBz584opWjZsiWHDh3K93Hr\n16+nZ8+ehISEULVqVa6//nrPBS0qhfjEFO763xpe/m4nt72/mm+3HLY7JK936nwGzy7cytD3VvPG\nkgRGTSv/Sai3HjpNRpaTjQdPyaTXpSBJWkWXPYH1Bx/A2LEQFGR3RKICqVsXfvwRYmNh5EgZ9ihE\nRRDoUmBKKZVz2+FwkJWVhZ+fH06nM2edCy4//imlPBeoqHTi9h5HW/MmZzo14z5ez7D3VvFRXCIn\nzqbbG5yX2X8qi3/O3USXF5Yw/Zf9ZE837YliHq7bv5DpZNmO5HLdX0UlSVpFde4cfPghtGoF48fD\ngAFmnjQhyliVKqYVTWt45x27oxFClLcGDRqwfft2ALZt20ZSkimMExsby5IlS0hLS+Ps2bOsWLHC\nzjBFBdSlWS2CAhz4WeXdb+/cmJPnMnj6qy10ev5H/jzjV17/cRdv/LirUrberN5zjPs/jqf3qyt4\nZnUaX21Iov8VDXh5yOUEW8fNE8U8ujSrRaC/A4f1m8289Qd49YedlfI1KQ0Zk1aRJCXB11+bSg5L\nlpjyex06wPvvQ+/eIL9winISEQG9epm33uuvy1tNiIqsd+/eLFy4kKFDh9K2bVuioqIAiImJoW/f\nvgwbNoyIiAg6dOhgc6SioomNCmP63R35cftRImqGEBzgR7VgfzSQkHyGJTuSWWK12ry7Yg+zRnex\nN2APik9M4Y5pa8nSGgX0jvLnlXt6UCMkAIBmdavmTEJd3mPEXCe9Tj6dxoerE3lzSQJTVu6VedOK\nQZI0X5eQALNmwYIFsH69Wda0qenaeOut0KOHFAwRHtG7t/mNICkJGja0OxohRElERkby5Zdf5tx+\n/vnn3d43ZcoUt48fO3YsY8eOLd8gRYV25kImB1POkZRynmWJGaxatJ2DKec4mHKepJTzHM/TrTHA\nTxFZM4TuLWpx+nwmW5JOoal8c3TF7T2Otjo1asDfQU6CBpdOQl3esvf3zrKEnGXZr4kkaUUjSZov\nOnsWZs+GGTPg559Ns0XXrvDiiyYxi4mRpgzhcdnTLe3cKUmaEEII906dz8hJwg5al6STVhJ28jwn\nz2XkWj9o934iw0KIrBlCmwY1aBgW4nIJpU7VIBxWv7r4xBRGTYsjI9OZ063vAzuepA2yuximZzpx\navg5KZOE5DO0qFvV9rj8HYpMp8bfT+ZNKw5J0nzNG2/Av/8NKSlmvNnEiXDHHRAp8yMJe4WHm7+n\nTtkbhxBCCHtorTl5LiNX4nXxYhKz1AuZuR4TEuBHw7AQIsNCuLJxTRqGhRJZ0yRhv2/fQP8+1xe5\nII1rN7vKVqLf9bnXrx7Mv+dv5Lb3V/PhvZ1oG1nD1rj+3b8NT361hUd7R1eq16S0JEnzJcuXmxmE\ne/QwiVr37tJiJrxGdq9al6JvQgghKph1+08wf8Mh6lYLItDfkdMClt0l8Vx6Vq71qwb5mySsZgid\nm4abJMylJSwsNCDfJOzUXlXsiqGe7tbnTVyfe8aRXby5STP8/dUMbB/JkNiGth2XIbEN+b/5W1i2\nI5mOTcIr7etTXJKk+ZJ0qx92ZCS0aCEJmvAqKVbRpjD57hVCiAopPjGFEVPiyHTqnGXVg/1pGBZK\nVK0qdG9RO1dLWKOwUKqH+MvUDDaoX8XBhP6tGfdRPJ+s/Z15vx30aNGOw6fOs3bfCdbsO8GKXX+Q\npWHNvhOMmhYnxUOKSJI0X9KrF9x/P7z3Hnz6qSmrf9NN0LMnREVJ0iZsdeyY+Zvd7VEIIUTFErf3\neE6C5lDwYI8W/K13K5ujEvlJSD5zyfxo5ZEcaa1JPH4uJylbu/84B06cB6BakD91qgehIFdBF0nS\nCidJmi9xOMxEVI88Au++axK1uXPNfeHhpnKD66VtW6hWzd6YRaVx4ID526iRvXEIIYpGKUW77Io/\nokCxsbF2h+AVujSrhVJmXsxAfwfXRde1OyRRgC7NauUkR2U5P9q6/Sf4ZvNh/P0cHD5pWsySU82k\n9uFVAunUJJw/dWtKp6bhXBZRnQ0HTl5S0EUUTpI0X9SyJbz6KkyaBNu2mbFqGzfC5s2m4uOZMxfX\njYqC1q0hOtoUGsm+REZKaX5Rpn7/HUJDoZZ89wrhE7TWbN68udy2P3nyZEJDQ7nnnnvKbR+eUhGe\nQ1no0LgmIf5+tIqoxlO3xEhriJdrVb8aGrimRW0eKaOiHUu2H2X0h+tyWujCQwO5Jro2nZqG07lp\nOM3rVL2ke2tlLuhSGpKk+TKloE0bc8nmdEJioknYNm+GrVtNTfRffsmdvIWGmsQtb/IWHQ3Vq3v+\nuQifl5gIjRtLr1shfFlSUhLjxo2jQ4cObNq0iejoaAYOHMjkyZM5ceIEEydO5KeffsqVfA0aNIi3\n336byMhIpkyZwsKFC6lXrx7h4eHExMTY+4REmTp6+gLnMrIY3MG+IhSi6HYfTQXgjq5RZfZ6vbMs\nISdBcyj48zVNeOCGloU+rjIXdCkpSdIqGofDTGbdtCn0739xudZw6BDs2mWStuzLunXwxRe5S/LV\nr38xabvsMrjySmjfHmrYV8JVeL/sJE0I4dsOHDjApEmTmDBhAiNGjGDRokXMnDmTZcuWMXXqVFq3\nbu32cVu3bmXx4sXMmTOHrKwshg8fLklaBbPLOulvafPcW6Jodh81P863qlc2Q19+P36OjQdP4ucw\nfV5N18XaZbJtcSlJ0ioLpUwXx8hIuOGG3PdduAB79uRO3nbuNMnbiRMX12vWzCRrV14JHTqYCbSl\nlJ/A5Pjbt8Of/2x3JEKI0oqMjCQ6OhqAFi1a0LlzZ5RStGzZkkOHDuWbpK1fv56ePXsSEhICwPXX\nX++pkIWH7E42J/2SpPmGXUdTCfJ30Cg8tEy2N+mHnQT4OXh7ZAd2Hk2VrovlTJI0AUFBEBNjLnkd\nOQK//Zb7Mm/exfvbtjVJ3623Ir3cKq/ERDh71rwdhBC+LTAwMOe6UirntsPhICsrCz8/P5wuvS8u\nXLiQa31RcSUkpxJeJZBaVYPsDkUUwc6jqbSoW9W0fJXSF/EHmL/hEIOvjKRXTD16xdQrgwhFQaRy\nhChY/fqmzP+//gWffw4JCXDyJCxdCs89Z1rmpk2DPn3oMmIEvPWW3RELG2zcaP5KkiZExdegQQO2\nb98OwLZt20hKSgJMBcQlS5aQlpbG2bNnWbFihZ1hinKw++gZWkgrms/YffQM0WXQ1TE+MYV/fLEJ\ngG82HyY+MaXU2xSFkyRNFF+NGqb17Mkn4dtvzQRZX33Fhbp14aGHTLESUaksXw7BwaYnrBCiYuvd\nuzenTp1i6NChzJkzh6ioKABiYmLo27cvw4YN49FHH6VDhw42RyrKktaaXUdTia4nSZovOJuhOXI6\nrUyStB+3HSV7/vLMLDPPmSh/0t1RlF5oKPTvz+mZM6m+Y4dpaROVhtawaBFcfbVJ1IQQvisyMpIv\nv/wy5/bzzz/v9r4pU6a4ffzYsWMZO3Zs+QYpbPFH6gVOp2XSsq7Mv+oLDp0xXZLLIqnO7i3pUGU7\n35oomCRpovScThgzhobz5sHo0dCtm90RCQ9avRp274YnnrA7EiGEN6lI86QJKRria5JykrTSJ9X7\nj58jPDSQP1/ThC7NakuxEA+RJE2UTno6TJgA06fz+4gRNJ4yRSbKqmSmTzeNqUOH2h2JEEKI8pI9\n51YL6e7oE5LOOAkJ8COyZkiptpOZ5eSn3X9wU9uIIs2HJsqOJGmi5FauhHHjTO314cPZd++9NJYE\nrVI5cgQ+/hjuvhuqVcAeMJ+s+Z35G5JKtY1th08TEyETxAvfIJNZi/zsSj5DzdAA6khlR5+QdMZJ\ny3rVcJSysuNnvx7gdFomjcJLl+yJ4pPCIaJkPvwQrrsOzp+Hb76Bzz5DBwTYHZXwsLfeMo2pjz9u\ndyTlY/6GJLYdPl2qbcREVGdA+8gyikiI8nfgwAFGjRrF3Llz2bdvX85k1o899hhTp07N93Guk1m/\n/vrrbNmyxYNRi/KWcPQMLetWlWkWfETSGV3qro7xiSlMWGCKwb21NEGqOnqYtKSJ4tEaXn8dHnvM\nVHj8+mvT101UOikpMHkyDB4MLStwD4iYiOp8dl9Xu8MQwmNkMmuRl9aaXcmp3NQ2wu5QRBGcPJfO\nqQu61EVD4vYeJ9Mq65hd1VHGo3mOJGmi6LQ2TSavvgpDhsBHH0GINH9XVv/+N5w+DU8/bXckQoiS\nUErRrl07t/e5Ll+4cCFPuFQG2rlzJwCTJk3KWda3b9+c6++//36ubbmu56tiY2PtDsFWx8+mc/Jc\nhhQN8RG7jlpFXkrZkta2gemqr5CqjnaQJE0U3WefmQTtwQfhjTfAIb1lK6t16+Dtt2HMGLjiCruj\nEUKUhNaazZs351qWlJTEgw8+mFNq/8knn+S6666jT58+Offde++9rFy5kpdffplt27YxcuRIFi1a\nxKlTp3jqqaf45JNPyMrKYvjw4QwbNqxCVHesCM+hNHbnnPRLkuYLdlpFXkrb3XHTwVMA9I6px33X\nNZdWNA+TJE0U3RdfQKNGprujJGiV1unTcNttEBkJL7xgdzRCCE/r3bs3CxcuZOjQobRt29btZNYR\nEREymXUFsju5bE76hWfsPppKsB80qFHyyUsTUrJ4/dfdACzZkUzHJuG0qFuVGiFSf8BTJEkTRXfu\nnCnh5+dndyTCJunpiiFDIDERVqyA8HC7IxJClCWZzFq4s/voGaoF+1O3mlR29AW7jqYSWdVRqiIv\nO05k4bTGo2U5Nc8v2s4Li7fTql41rmoSRscm4VzVJJzImiHEJ6YQt/c4XZrVkta2MiTNIaLoOnSA\nbdvMrMWZmXZHIzwsMxOeey6GH3+E//0Pune3OyIhhCdMmDCBPXv2AHDjjTeSkpLC6dOnmT17tq1x\nPfnkk3z//fe2xlBZ7E5OlcqOPmT30TNEVivdKX7rcD+CAhz4KQj2d/BM/xge7RVNnWpBfLk+iYdn\nb6D7xKVc9Z8fGPbeKl75biejpsZJBcgyJC1pougmTIDkZJg4EbZuhXnzwF/eQpVBZiaMGgU//VSH\n118386IJIXxbQYVD8po3b17O9WuvvTbnumtLmx0WLFjgkf1U9sIhCcln6Nm6nt1hiCI4duYCx8+m\nE9kosFTbaRHmx6zRXdy2kGVmOdlxJJV1+08w+9cDHDubDkBappMn5m3ikV7R9Ghdl+AA6XlVGnKG\nLYouIACmTIG2beHhh+Gdd8xfUaFlJ2hz5sC4cXt4+OHmdockhCgDeQuHnDt3jscff5yjR4/idDq5\n77776Nu3L3/60594/PHHadOmDTfeeCOzZ8/mhRdeYNmyZTRp0oSuXbty7NgxevfuTY8ePQAYP348\nffv25YYbbsjZ/q+//so777xDrVq12LlzJz179qRly5bMmjWLtLQ03nzzTRo1apSrWAlAp06dWLt2\nLVprXnjhBdauXUtkZCRaawYNGpSzXnmqzIVDlu1M5tiZdEICpfOVL/h60yHAVGQsrdioMLfdF/39\nHLSNrEHbyBq0a1iTUdPiSM90opTi6Ok07p+1niqBfvRpU5/+VzTg6pa12XTwlHSJLCZJ0kTx/fWv\nZn60Z56BQYOgcWO7IxLl6MEHTYL28stw1VUHAEnShKiIfvnlF+rWrcvkyZMBSE1NzXfdRx55hISE\nBL744gvAJGAfffQRPXr0IDU1lY0bN7ptZdu1axfz58+nRo0a3HTTTQwePJhPP/2Ujz/+mE8++YTx\n48fnu88lS5awf/9+5s2bx/Hjxxk4cCCDBg0q5bMWBYlPTOG+mfEAfLLmALdeESkn2F4sPjGF577e\nDsDnu9IZkphS7q9XbFRYrha3KxrWIG7vCRZuPMTiLYf58rckqgb5cT7DidaaQH8Hs0Z3kfdREcjP\nIqL4lILXXoOTJ81caaLCmj0b3n8fxo83U+QJISquli1bEhcXx6uvvkp8fDzVqhW9kl/Hjh05cOAA\nx48fZ/HixfTq1Qt/N93h27RpQ506dQgMDKRhw4Z069YtZ99JSUkF7iM+Pp6bb74ZPz8/6tatS6dO\nnYr3BEWxmcmMnQBkOs1kxsJ7uU4+neXEY69XbFQYD9zQgtioMPz9HFzdsjb/HXo5vz7Vi2l3XUVI\noD9ZTo1TQ0amvI+KSpI0UTIxMRAdDd9+a3ckopycOQOPPgodO8Jzz9kdjRCivDVp0oTPPvuMli1b\n8sYbb/Duu+8W6/H9+vXjm2++4auvvmLgwIFu1wkMvDhOxuFw5Nx2OBxkZWUB4O/vj9NKDLTWZGRk\nlOTpiDLQpVktAv3NqaLW0LGJtH54sw6NawKmq6O/A9snnw7y96N+jWBOnUtHKfBTMil2cUiSJkpG\nKQgMlBrsFdiHH8KRI2b+cqkPI0TFl5ycTHBwMLfeeit3330327dvz3fdKlWqcPbs2VzLBgwYwMcf\nfwxAixYtShxHgwYN2LZtGwBLly4l06omHBsby7fffktWVhZ//PEHa9euLfE+RNFkd2Ub2L4BGth/\n/JzdIYkCnDpvPivDrmrIPzoG296lMPl0GmNmrqN21SCm3XUVf+vTSro6FoOceoni0xomT4YtW6Bf\nP7ujEeXks8/giivg6qvtjkQI4Qm7d+9m0qRJOBwO/P39efrpp/Ndt2bNmrRv355BgwZx9dVX89hj\nj1G7dm2aNWuWUzykpIYMGcLDDz/MyJEj6dy5MyEhIQD07NmTNWvWMHjwYKKiorjqqqtKtR9RNLFR\nYXRoXJN9x87yxo+7GdC+AUH+UrXPG32z+TDhVQJ5YVA7fv5ppa2xpGVkMfajeE6ey+CLv3SlTYMa\n9LxMKoQWhyRpoviefx6efhpuvBH+9S+7oxHlQGuIj4fRo+2ORAjhKd27d6e7mwkQP/jgg5zr3333\nXc71l156Kdd658+fJzExkZtuusnt9jt27EjHjh3dbtf1vtq1azNr1qyc+x555BHATBnw5JNPFucp\niTKilOLvN7bmjv+t4dM1v3NP96Z2hyTySMvIYsn2owxoH4m/n70d5eL3n+Dp+VvZdvg0793RgTYN\natgaj6+S7o6ieD75xCRoo0bBokVQjIHlwnekpcG5c1BPfvQSQhTB6tWr6d+/P7fffnuxCo4I39G9\nRS26NqvF28sSOJeeaXc4Io/lO//gXHoWt7SLsDWO+MQUbpsSx7bDp/F3KOpUC7Y1Hl8mSZooutOn\n4R//gNhYM2DJIW+fiiooCPz8TPEQIYQoTNeuXfnhhx+488477Q5FlBOlFI/f2IpjZ9L54Jf9docj\n8sju6tilmb21AlwrTDq1lkqOpSBn2aJozp+HwYPh8GEzibWf9EevyBwOaNIEEhLsjkQIIYS3iI0K\no9dldXl/xR5OnZOqm94iu6vjjW3q297VsUuzWgS5VAS9vKF0dSwpSdJE4S5cgKFDYelSmDEDOne2\nOyLhATExYBVYE0IIIQB4rE8rTqdlMuWnPXaHIize0tURTCL/yZgujOzUGKXgkzW/o7W2OyyfJIVD\nRMEyMmDECDP+bMoUkK4slUabNmYavMxMKcEvREWklKJdu3Z2h+ETYmNj7Q7Ba1wWUZ3+VzRg+s/7\nuadbU+pUC7I7pErPW7o6ZouNCiM2KoymtUN5YdEO/vfzPkZf08zusHyOnHqJgs2cCV99Ba+9BmPG\n2B2N8KBq1UyObs0pK4SoYLTWbN682e4wfMI999xjdwhe5dHe0Xy96RD3fbSOJ2+JkXmvbLR6zzG+\n3XKY66Pr2t7VMa8x1zRj3f4UXly0nb1/nGVIbEN5rxSDd72awvv8979w+eXw8MN2RyI87OBBqFED\nAgLsjkQIIYQ3OXE2HYVi/e8nGTU1jvjEFLtDqpTiE1O4e/paMrI0K3Yle93roJTizq5RODV8svZ3\nRk2T90pxSJIm8nfmDOzbB716gVJ2RyM8bOVKU8hTXnohhBCu4vYeJ8saZ5SR5ZQKfjZxraSYkeWd\nlRR/3XeC7BFpGZnyXikOSdJE/hYuNAOSeva0OxLhYTt3wtatMHCg3ZEIIYTwNjERZi48BQT4O+jS\nrJa9AVVSXZrVIjC7kiJwZaOa9gbkxr5jZwFwKHmvFJeMSRP5C7YmIDx2zN44hMd99JEpwz94sN2R\nCCGE8DYJyebE+57uTeh3eQMZZ2ST2KgwZo3uwhfxB/l07e/sPXaWbi1q2x1Wjn3HzvLt1iP0bF2X\nDlFhdGlWS94rxSBJmsjfTTdBp07w2GPQpw/Ur293RMIDsrLMXOV9+kBkpN3R2O9ezzIAACAASURB\nVG/b4dPc9v7qct3HgPaR3N65cbnuQwghykL8/hO8uyKB6HpVmXBrG7vDqfRio8Lo0Lgm2w6f5p1l\nCZw8l07X5vYnavGJKYyfuwk/pXhxSDvqVgu2OySf49Hujkqp6UqpZKXUFpdl4UqpH5RSu62/kmJ7\ni+BgeO8905L24Yd2RyM8ZOlSUzREipmZ5Ckmonq57mPb4dPM35BUrvsQQoiyEJ+YwsipazhxNoN9\nx85KEQgvoZSiZ+u6HD6VxqTvdzFqWhwJKVm2xROfmMLIKXEkJJ8h06k5cOK8bbH4Mk+3pM0A3gZm\nuiz7J7BEaz1RKfVP6/Z4D8cl8hMTY/4eOWJvHMJjZsyAmjVhwAC7I7Hf7Z0bl3sLV3m30gkhRFmJ\n23ucDGtelowszZSVe5g8KhY/h1SYsltmlnldNKZAx44T9iVpcXuPk54djzYFTaSbY/F5tCVNa70S\nOJFn8QAgu5nmQ0BKFXiTJUvM3/37bQ1DeEZampkWb/jwi0MShRBCCDCFKoL8HTiUqfz73daj3PrW\nz6yRin22qxlq5svJLtDROtzPtli6NKtFdt4uxUJKzhvGpNXTWh8G0FofVkrVtTsgAZw/D3//O7zz\njpkn7fXX7Y5IeMDSpXDuHAwaZHckQgghvE12oYq4vcfp0jScpFNpTFy0ndumxHFLuwieuLk1DcNC\n7Q6zUjp5LgMF/LVHS66NrkPqvo22xRIbFUaretVIvZDJGyOulFa0EirrJK22Umqdy+0pWuspZbwP\nUZ4yMsz4s2efhQMH4G9/gxdegKAguyMTHrBgAVStCjfcYHckQgghvFFsVFjOSXcs0Puyery/cg/v\nrdjDj9uPct+1zRh3fXNCA72hHaDyWLv/BG0ja/Bo72gAlu+zN560TCdXNKopCVoplPUn6JjW+qpi\nPuaoUirCakWLAJLLOCZRVKmpcO21sGGDqer40Udw3XV2RyU8JC0N5s+HG2+UnFwIIUTRhAT68Uiv\naIZf1YiJi3fw5tIE5qw7yG0dGxHor+jSrLacqJezNXuP8+v+FPq2qWd3KDmOnkojLDSA+MQUef1L\nyBsms14A3G1dvxuYb2MsldsHH5gE7eOPIS5OErRK5qWXTH2Yv/zF7kiEEBXB5MmTmTFjxiXLk5KS\nGOQFfao7depkdwgVSoOaIbw58krm/qUrVYL8eGPJbl7+bhcjpqzm5wSZb7W8xCemcOf0tWQ5Nd9v\nO+oVFTdX7znGuYwsfvv9JKOmxXlFTL7I0yX4PwVWA62UUgeVUn8GJgK9lVK7gd7WbWGHr76CFi1g\n1CgzIlhUGgsXwjPPwMiR0LOn3dEIIYTwVbFR4Qy6MpLss4iMLM3d09fywKz1fLf1CBcy7as6WBHF\n7T1OeqappOh0mkqKdltnJWUaSMtwsmyHdJIrCY92GNZaj8znLjkt9AZKQbVqdkchPGz2bLjrLoiN\nhWnT7I5GCGGXpKQkxo0bR4cOHdi0aRPR0dEMHDiQyZMnc+LECSZOnEi7du2YPHkyoaGh3GNNpjho\n0CDefvttIiMjmTJlCgsXLqRevXqEh4cTY03jsnXrVv7v//6P4OBgOnTokLPPu+++myeeeILWrVsD\ncOedd/LUU0/RqlWrnHUSEhJ4+umnycjIwOl08tprrxEVFcVDDz3EkSNHSE9PZ9SoUQwbNgwwLWR3\n3HEHK1asIDg4mDfeeIPatWtz8OBBxo8fT1ZWFt27d/fQUa2cujavTVBAAhmZTvz8HPRsXZe4vcf5\nZvNhqgX707dNfQa0j6Rr81pSvr+U6lYz4xMU3lNJsVvz2rzjn8CFTCcamLl6P63qV6Pf5REoaQQo\nMhnVKS764w/YvBmSk6GuFNmsDN58Ex55BK65xhQNCZWiXEJUagcOHGDSpElMmDCBESNGsGjRImbO\nnMmyZcuYOnUqb775Zr6P3bp1K4sXL2bOnDlkZWUxfPjwnCTt6aef5oknnqBjx45MmjQp5zGDBw9m\n/vz5tG7dmv3795Oenp4rQQOYM2cOo0aNol+/fmRkZJCVZVpi/vOf/1CjRg3S0tIYOXIkvXv3pmbN\nmpw/f57LL7+chx56iFdffZW5c+dy33338d///pfbbruN/v378+mnn5bD0RPZclWBbFaL2KgwMrOc\nrNpznPkbDrF4yxE+jz9I7apB9Ls8gv7tG6Cdmrh9J3LWF4WLT0xh8vI9hAQ4GHNtM66LrusVxy42\nKoxZY8zrH1EjmBmr9vPXT39j/oYkhl/ViN3JZ+R1LgJJ0sRF06dDt25w++2waBEEBtodkSgnWVnw\n6KPw1lswcCB88gmEhNgdlRDCbpGRkURHm+pwLVq0oHPnziilaNmyJYcOHSrwsevXr6dnz56EWF8m\n119/PQCpqamkpqbSsWNHAPr168fPP/8MQJ8+fXj//ff529/+xpdffsmAAQMu2e4VV1zB1KlTOXr0\nKL169SIqKgqAWbNmscSay/PIkSMkJiZSs2ZNAgICuM4aUx0TE8Pq1WbC+N9++41XX30VgFtvvZXX\nXnutxMdJFM61CiSAv5+Da6PrcG10HZ7PaMuyHcks2HiIT9b+zoxV+1GYDj2B/g5mje4iJ/CFiE9M\nYeTUONIznfg7lNckaNlcX//+VzTgg1/28/J3O/hxezJKQZC8zoXyhsIhwltcdRW8/76ZwFr+eVVY\nZ86YxOytt8wMC198IQmaEMIIdPlxTimVc9vhcOS0YPn5+eF0OnPWu3DhQq7H5KW1zreLU0hICF27\ndmXZsmV899133HLLLZesc8stt/DWW28RHBzMfffdx5o1a/j111+Ji4vj448/Zu7cubRu3Zr09HQA\n/P39c/bncDjIzMwsMD7hecEBftzULoJ374hl3l+6EeCn0IBTQ0am0yvGVXm7uL3Hycgei6a9Yyxa\nfvz9TEvf3d2aAKDldS4SSdJEbn/6E/TqZeZJS5aBnhXNyZPQp49pKH3nHZg0Cfz87I5KCOFLGjRo\nwPbt2wHYtm0bSUlJAMTGxrJkyRLS0tI4e/YsK1asAKB69epUrVqV9evXA/DNN9/k2t7gwYOZOHEi\nbdu2pUaNGpfs78CBAzRs2JBRo0Zxww03sGvXLlJTU6levTohISHs3buXTZs2FRr3lVdeyeLFi93G\nIOzx0+4/GDVtDYF+DgL9HPgp7xlX5e26NKtFgJ85jfd3+MYx69s2gkA/80OJUsonYraTdHcUF6Wm\nmhJ/S5ZAVJRUeKxgjh0zc6Bt3gyffw6DB9sdkRDCF/Xu3ZuFCxcydOhQ2rZtm9P9MCYmhr59+zJs\n2DAiIiJyFQj5z3/+k1M4JG/RjjZt2lClShUGDhzodn/fffcdX3/9Nf7+/tSuXZtx48YREhLCnDlz\nGDx4ME2aNOHyyy8vNO7x48czfvx4Zs2aRa9evUpxBERpaa2Z9tM+Xly8nZZ1qzHlrliOnUnPNYZN\nFCw2KoyXhl7OI59t4IEeLXzimMVGhfHpmC48/NkGUtMyaV1fitUVRJI0YaxaBUOHwuHDMHYsvPKK\nVHqsQI4cMQ2ke/aYmRZuvtnuiIQQ3iYyMpIvv/wy5/bzzz/v9r7g4GCmTJnidhtjx45l7Nixlyxv\n06YNc+fOzbl9//3351xPTk5Ga023bt3cbnP06NGMHj36kuXvvfee2/XXrl2bc71Pnz706dMHgIYN\nGzJr1qxc2xWedz49i3/O28T8DYe4qW19Xhl2BVWC/ImqVcUnEg1vckNrU+QtNMB3usTENgnnjRFX\nMuTdVXzwyz4e7NHS7pC8liRpAjIz4Y47TCfhuDjo3NnuiEQZOnDAzH126BB88w306GF3REIIYSxY\nsIA333yTv//97zgcMgKjojuYco77Popn2+HTPN4nmgduaCHjBEuherA/oYF+HD6VZncoxRIbFUav\ny+rx/oq9jOocRVgVKVTnjiRplV1qKjz8MOzbBx99JAlaBZKVZV7Sf/wDLlyA7783xTuFEL7l999P\n89JLm2jYsD01alTNdZ9flQx63JKOr+Y3/fv3p3///naHITxg5ur9vLhoBwqYdtdV9Lysnt0h+Tyl\nFDVDAvg54Q/iE1N8qiXy7ze24sbXV3LfR+sYf9NlPhW7p0iSVlmdPWsqR7z0Ehw/Dk8+aVrThM87\nfBg+/NBMTL1nj8m7//c/aNPG7siEECWxcuUB3nknDogDuhIU1AWHw+repPxo3CqA8W+mEFbXWdBm\nhLCF1ppnv97GB7/sB0zp9Zqh0nJSFuITUzhyOg3nKRg1Lc6nStqfuZCJQ8Ha/Sk+F7un+Ohvb6LE\nTp0yiVnz5jB+PHTsCGvXwnPP2R2ZKIXDh01S1q8fNGoETzwBkZEwdy6sXi0JmhC+7I472rB372ia\nNAkDVnPhwmucP7+X8+fh/DkHezYH8ODNdVi3IginpsgXIcrbufRMHp69ISdBA8jMktLrZSVu7/Gc\nz7KvlbT/ZvNhn43dU6QlrbJwOuGDD0xidvy4GaQ0dy7kqbIlfEN6OqxZA0uXmnFmv/5qljdubOY+\nGz0arPlohRAVQNOmNdm37898//1+brzxC2AeSlVH66FkZoaTmap45aGa9Bh8nrv/eZoAaagQNtt/\n7Cz3fRTPruRUbu/cmHnrD5KR6ZQS+2WoS7Na+DkUWU7tc8d1x+HTADLtQgEkSasMfvsNHnjANKl0\n7w6vv24mrhY+4+xZWL8efvoJli2DX36B8+fNLAmdOpmG0FtvhXbtZOYEISqyPn2acOHCo7z44lqe\neeYXYDpKtUPr67mQFsTSL0PZuCqIJ949QYOmWXaHKyqpJduP8shnG/BzKGb8qRPXRddhSIeGUmK/\njMVGhTGiYyNmrfmd6Xd39JnjuiXpFKv2HGdYbCRNaleV90Q+JEmryHbsMLMVT58OtWrBjBlw1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cPXqUFStW4OTkxMiRI7n33nsxGAzMmTOHZcuW4eHhwZQpUwgLC6vW6ybUXExSJgDhwWIkrbq6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\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D6/Hycufrr8Nq6qnXCpHxGXg42dHWx9XWodRaoTGJNHVV6ORbt5YFEXWbJGnWtGeP/rNX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\n",
      "text/plain": [
       "<Figure size 1008x1000.8 with 11 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connection to \\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\\East_Kimberley_borehole_data.sqlite is closed. Temporary working copy removed.\n"
     ]
    }
   ],
   "source": [
    "# Define the database path. Check this to ensure its up to date with the variables above.\n",
    "# Variable definition applied here just so this cell runs standalone\n",
    "DB_ROOT = r\"\\\\prod.lan\\active\\proj\\futurex\\East_Kimberley\\Working\\SharedWorkspace\\Bores_working\\compilation\\spatialite\"\n",
    "DB_PATH = os.path.join(DB_ROOT, r\"East_Kimberley_borehole_data.sqlite\")\n",
    "\n",
    "# connect to database\n",
    "con = makeCon(DB_PATH)\n",
    "\n",
    "bhid = bhname = 635735 # ENO for KR33\n",
    "data = extract_all_boredata_by_simple_query(con, bhid)\n",
    "drawCompLog(data)\n",
    "\n",
    "# Close the DB connection\n",
    "closeCon(con, DB_PATH)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
